Claude Integrations

https://www.anthropic.com/news/integrations

by bryanh • 1 year ago

734 257 1 year ago

behnamoh• 1 year ago

That "Allow for this chat" pop up should be optional. It ruins the entire MCP experience. Maybe make it automatic for non-mutating MCP tools.

pcwelder• 1 year ago

In the latest update they've replaced "Allow for this chat" with "Always Allow".

avandekleut• 1 year ago

MCP also has support for "hints" which note whether an action is destructive.

arjie• 1 year ago

The cookie banner type constant Allow Allow Allow makes their client unusable. Are there any alternative desktop MCP clients?

rahimnathwani• 1 year ago

https://github.com/patruff/ollama-mcp-bridge

jarbus• 1 year ago

Anyone have any data on how effective models are at leveraging MCP? Hard to tell if these things are a buggy mess or a game changer

striking• 1 year ago

Claude Code is doing pretty well in my experience :) I've built a tool in our CI environment that reads Jira tickets, files GitHub PRs, etc. automatically. Great for one-shotting bugs, and it's only getting better.

xnx4• 1 year ago

Integrations are nice, but the superpower is having an AI smart enough to operate a computer/keyboard/mouse so it can do anything without the cooperation/consent of the service being used.

Lots of people are making moves in this space (including Anthropic), but nothing has broken through to the mainstream.

WillAdams3• 1 year ago

Or even access multiple files?

Why can't one set up a prompt, test it against a file, then once it is working, apply it to each file in a folder in a batch process which then provides the output as a single collective file?

xnx4• 1 year ago

You can probably achieve what you want with https://github.com/simonw/llm and a little bit of command line.

Not sure what OS you're on, but in Windows it might look like this:

FOR %%F IN (*.txt) DO (TYPE "%%F" | llm -s "execute this prompt" >> "output.txt)

TheOtherHobbes• 1 year ago

I've just done something similar with Claude Desktop and its built-in MCP servers.

The limits are still buggy responses - Claude often gets stuck in a useless loop if you overfeed it with files - and lack of consistency. Sometimes hand-holding is needed to get the result you want. And it's slow.

But when it works it's amazing. If the issues and limitations were solved, this would be a complete game changer.

We're starting to get somewhat self-generating automation and complex agenting, with access to all of the world's public APIs and search resources, controlled by natural language.

I can't see the edges of what could be possible with this. It's limited and clunky for now, but the potential is astonishing - at least as radical an invention as the web was.

pglevy• 1 year ago

I've been using Claude Desktop with built-in File MCP to run operations on local files. Sometimes it will do things directly but usually it will write a Python script. For example: combine multiple.md files into one or organize photos into folders.

I also use this method for doing code prototyping by giving it the path to files in the local working copy of my repo. Really cool to see it make changes in a vite project and it just hot reloads. Then I make tweaks or commit changes as usual.

arnaudsm• 1 year ago

I get often ratelimited or blocked from websites because I browse them too fast with my keyboard and mouse. The AI would be slowed down significantly.

LLM-desktop interfaces make great demos, but they are too slow to be usable in practice.

xnx4• 1 year ago

Good point. Probably makes sense to think of it as an assistant you assign a job to and get results back later.

boh• 1 year ago

I think all the retail LLM's are working to broaden the available context, but in most practical use-cases it's having the ability to minimize and filter the context that would produce the most value. Even a single PDF with too many similar datapoints leads to confusion in output. They need to switch gears from the high growth, "every thing is possible and available" narrative, to one that narrows the scope. The "hallucination" gap is widening with more context, not shrinking.

mikepurvis• 1 year ago

That's a tough pill to swallow when your company valuation is a $62B based on the premise that you're building a bot capable of transcendent thought, ready to disrupt every vertical in existence.

Tackling individual use-cases is supposed to be something for third party "ecosystem" companies to go after, not the mothership itself.

Etheryte• 1 year ago

This has been my experience as well. The moment you turn internet access on, Kagi Assistant starts outputting garbage. Turn it off and you're all good.

fhd22• 1 year ago

Definitely my experience. I manage context like a hawk, be it with Claude-as-Google-replacement or LLM integrations into systems. Too little and the results are off. Too much and the results are off.

Not sure what Anthropic and co can do about that, but integrations feel like a step in the wrong direction. Whenever I've tried tool use, it was orders of magnitude more expensive and generally inferior to a simple model call with curated context from SerpApi and such.

loufe• 1 year ago

Couldn't agree more. I wish all major model makers would build tools into their proprietary UIs to "summarize contents and start a new conversation with that base". My biggest slowdown with working with LLMs while coding is moving my conversation to a new thread because context limit is hit (Claude) or the coherent-thought threshold is exceeded (Gemini).

medhir• 1 year ago

you hit the nail on the head. my experience with prompting LLMs is that providing extra context that isn’t explicitly needed leads to “distracted” outputs

ketzo• 1 year ago

I mean, to be honest, they gotta do both to achieve what they’re aiming for.

A truly useful AI assistant has context on my last 100,000 emails - and also recalls the details of each individual one perfectly, without confusion or hallucination.

Obviously I’m setting a high bar here; I guess what I’m saying is “yes, and”

energy123• 1 year ago

There's a niche for the kitchen sink approach. It's a type of search engine.

Throw in all context --> ask it what is important for problem XYZ --> curate what it tells you, and feed that to another model to actually solve XYZ

roordan• 1 year ago

This is my concern as well. How successful is it in selecting the correct tool out of hundreds or thousands?

Different to what this integration is pushing, the LLMs usage in production based products where high accuracy is a requirement (99%), you have to give a very limited tool set to get any degree of success.

bredren2• 1 year ago

Had been planning a custom mcp for our orgs’ jira.

I’m a bit skeptical that it’s gonna work out of the box because of the amount of custom fields that seem to be involved to make successful API requests in our case.

But I would welcome, not having to solve this problem. Jira’s interface is among the worst of all the ticket tracking applications I have encountered.

But, I have found using a LM conversation paired within enough context about what is involved for successful POSTs against the API allow me to create update and relate issues via curl.

It’s begging for a chat based LLM solution like this. I’d just prefer the underlying model not be locked to a vendor.

Atlassian should be solving this for its customers.

viraptor• 1 year ago

You can also do the same thing locally: https://github.com/sooperset/mcp-atlassian Either with the cloude app, or some other system with any tool-using LLM you want.

bredren2• 1 year ago

I'm familiar with that MCP and was planning to build on top of it.

I hadn't realized but the new integration seems to actually just be an official, closed-source MCP produced *by* Atlassian.

sooperset's MCP is MIT licensed, so I wonder how much of the Atlassian edition is just a lift of that.

There's a comment [1] on the actual integration page asking about custom fields, which I think is possibly a big issue.

At first I thought the open-source version would get crushed by an actual Atlassian release, but not if Atlassian doesn't offer all the support for it to work really well no matter what customizations are fitted into each instance.

My hypothesis is that it takes custom code to make this work, and using the off-the-shelf for Jira won't work. Hoping to be proven wrong though, as it would be less work for me on that front.

[1] https://community.atlassian.com/forums/Atlassian-Platform-ar...

rubenfiszel2• 1 year ago

I feel dumb but how do you actually add Zapier or Confluence or custom MCP on the web version of claude? I only see it for Drive/Gmail/Github. Is it zoned/slow release?

throwaway314155• 1 year ago

edit: <Incorrect>im fairly certain these additions only work on Claude Desktop?</Incorrect>

That or they're pulling an OpenAI and launching a feature that isn't actually fully live.

rubenfiszel2• 1 year ago

But the videos show claude web

85392_school2• 1 year ago

This part seems relevant:

in beta on the Max, Team, and Enterprise plans, and will soon be available on Pro

joshwarwick152• 1 year ago

Created a list of remote MCP servers here so people can keep track of new releases - https://github.com/jaw9c/awesome-remote-mcp-servers

zhyder• 1 year ago

Is there any way to access this via the API, after perhaps some oauth from the Anthropic user account?

throwup2382• 1 year ago

The leap frogging at this point is getting insane (in a good way, I guess?). The amount of time each state of the art feature gets before it's supplanted is a few weeks at this point.

LLMs were always a fun novelty for me until OpenAI DeepResearch which started to actually come up with useful results on more complex programming questions (where I needed to write all the code by hand but had to pull together lots of different libraries and APIs), but it was limited to 10/month for the cheaper plan. Then Google Deep Research upgraded to 2.5 Pro and with paid usage limits of 20/day, which allowed me to just throw everything at it to the point where I'm still working through reports that are a week or more old. Oh and it searched up to 400 sources at a time, significantly more than OpenAI which made it quite useful in historical research like identifying first edition copies of books.

Now Claude is releasing the same research feature with integrations (excited to check out the Cloudflare MCP auth solution and hoping Val.town gets something similar), and a run time of up to 45 minutes. The pace of change was overwhelming half a year ago, now it's just getting ridiculous.

user_78322• 1 year ago

I agree with your overall message - rapid growth appears to encourage competition and forces companies to put their best foot forward.

However, unfortunately, I cannot shower much praise on Claude 3.7. And if you (or anyone) asks why - 3.7 seems much better than 3.5, surely? - Then I’m moderately sure that you use Claude much more for coding than for any kind of conversation. In my opinion, even 3.5 Haiku (which is available for free during high loads) is better than 3.7 Sonnet.

Here’s a simple test. Try asking 3.7 to intuitively explain anything technical - say, mass dominated vs spring dominated oscillations. I’m a mechanical engineer who studied this stuff and I could not understand 3.7’s analogies.

I understand that coders are the largest single group of Claude’s users, but Claude went from being my most used app to being used only after both chatgpt and Gemini, something that I absolutely regret.

airstrike• 1 year ago

I too like 3.5 better than 3.7 and I use it pretty often. It's like 3.7 is better in 2 metrics but worse in 10 different ones

joshstrange• 1 year ago

I use Claude mostly for coding/technical things and something about 3.7 does not feel like an upgrade. I haven't gone back to 3.5 (mostly started using Gemini Pro 2.5 instead).

I haven't been able to use Claude research yet (it's not rolled out to the Pro tier) but o1 -> o3 deep research was a massive jump IMHO. It still isn't perfect but o1 would often give me trash results but o3 deep research actually starts to be useful.

3.5->3.7 (even with extended thinking) felt like a nothingburger.

mattlutze• 1 year ago

The expectation that one model be top marks for all things is, imo, asking too much.

tiberriver256• 1 year ago

3.7 did score higher in coding benchmarks but in practice 3.5 is much better at coding. 3.7 ignores instructions and does things you didn't ask it to do.

garrickvanburen• 1 year ago

My current hypothesis: the more familiar you are with a topic the worse the results from any LLM.

fastball• 1 year ago

Seems clear to me that Claude 3.7 suffers from overfitting, probably due to Anthropic seeing that 3.5 was a smash hit in the LLM coding space and deciding their North star for 3.7 should be coding benchmarks (which, like all benchmarks, do not properly capture the process of real-world coding).

If it was actually good they would've named it 4.0, the fact that they went from 3.5 to 3.7 (weird jump) speaks volumes imo.

csomar• 1 year ago

Plateauing overall but apparently you can gain in certain directions while you lose on some. I've written an article a while back that current models are not that far from GPT-3.5: https://omarabid.com/gpt3-now

3.7 is definitively better at coding but you feel it lost a bit of maneuverability at other domains. For someone who wants code generated, it doesn't matter but I've found myself using DeepSeek first and then getting code output by 3.7.

ilrwbwrkhv• 1 year ago

None of those reports are any good though. Maybe for shallow research, but I haven't found them deep. Can you share what kind of research you have been trying there where it has done a great job of actual deep research.

Balgair5• 1 year ago

I'm echoing this sentiment.

Deep Research hasn't really been that good for me. Maybe I'm just using it wrong?

Example: I want the precipitation in mm and monthly high and low temperature in C for the top 250 most populous cities in North America.

To me, this prompt seems like a pretty anodyne and obvious task for Deep Research. It's long, tedious, but mostly coming from well structured data sources (wikipedia) across two languages at most.

But when I put this in to any of the various models, I mostly get back ways to go and find that data myself. Like, I know how to look at Wikipedia, it's that I don't want to comb through 250 pages manually or try to write a script to handle all the HTML boxes. I want the LLM/model to do this days long tedious task for me.

xrdegen• 1 year ago

It is because you are just such a genius that already knows everything unlike us stupid people that find these tools amazingly useful and informative.

greymalik• 1 year ago

Out of curiosity - can you give any examples of the programming questions you are using deep research on? I’m having a hard time thinking of how it would be helpful and could use the inspiration.

dimitri-vs• 1 year ago

Easy, any research task that will take you 5 minutes to complete it's worth firing off a Deep Research request while you work on something else in parallel.

I use it a lot when documentation is vague or outdated. When Gemini/o3 can't figure something out after 2 tries. When I am working with a service/API/framework/whatever that I am very unfamiliar with and I don't even know what to Google search.

emorning3• 1 year ago

I often use Chrome to valid what I think I know.

I recently asked Chrome to show me how to apply the Knuth-Bendix completion procedure to propositional logic, and I had already formed my own thoughts about how to proceed (I'm building a rewrite system that does automated reasoning).

The response convinced me that I'm not a total idiot.

I'm not an academic and I'm often wrong about theory so the validation is really useful to me.

risyachka• 1 year ago

What are you talking about

It is literally stagnated for a year now

All that changed is they connect more apis.

And add a thinking loop with same model powering it

This is the reason it seems fast - nothing really happens except easy things

tymscar• 1 year ago

I totally agree with you, especially if you actually try using these models, not just looking at random hype posters on twitter or skewed benchmarks.

That being said, isn’t it strange how the community has polar opposite views about this? Did anything like this ever happen before?

itissid• 1 year ago

I've been using it for pre scoping things I have no idea about and rapidly iterating by refeeding it a version with guard rails and conditions from previous chats.

Like I wanted to scope how to build a home made TrueNAS Scale unit, it helped me with a avoiding pitfalls like knowing that I needed two GPUs minimum to run the OS and local llms, and speed up config for a CLI back up of my Dropbox locally(it told me to use the right filesystem format over ZFS to make Dropbox client work).

It has researched how I can structure my web app for building payment system on the web(something I knew nothing about) to writing small tools to talk to my document collection and index them into collections in Anki in one day.

wilg• 1 year ago

o3 since it can web search while reasoning is a really useful lighter weight deep research

spaceman_20203• 1 year ago

Gemini 2.5 pro was the moment for me where I really thought “this is where true adoption happens”

All those talks about AI replacing people seemed a little far fetched in 2024. But in 2025, I really think models are getting good enough

antupis• 1 year ago

You still need "human in the loop" because with simple tasks or some tasks that have lots of training material, models can one-shot answer and are like super good. But if the domain grows too complex, there are some not-so-obvious dependencies, or stuff that is in bleeding edge. Models fail pretty badly. So you need someone to split those complex tasks to more simpler familiar steps.

iLoveOncall2• 1 year ago

Calling some APIs is leap-frogging? You could do this with GPT-3, nothing has changed except it's branded under a new name and tries to establish a (flawed) standard.

If there was truly any innovation still happening in OpenAI, Anthropic, etc., they would be working on models only, not on side features that someone could already develop over a weekend.

never_inline2• 1 year ago

Why would you love on-call though?

apwell23• 1 year ago

DeepResearch which started to actually come up with useful results on more complex programming questions

Is there a youtube video of ppl using this on complex open source projects like linux kernel or maybe something like pytorch.

How come none of the oss pojects( atleast not the ones i follow) are progressing fast(er) from AI like 'deepresearch'

WhitneyLand• 1 year ago

The integrations feel so rag-ish. It talks, tells you it’s going to use a tool, searches, talks about what it found…

Hope one day it will be practical to do nightly finetunes of a model per company with all core corporate data stores.

This could create a seamless native model experience that knows about (almost) everything you’re doing.

pyryt• 1 year ago

I would love to do this on my codebase after every commit

notgiorgi• 1 year ago

why is finetuning talked about so much less than RAG? is it not viable at all?

mring33621• 1 year ago

i'm not an expert in either, but RAG is like dropping some 'useful' info into the prompt context, while fine tuning is more like a performing mix of retraining, appending re-interpretive model layers and/or brain surgery.

I'll leave it to you to guess which one is harder to do.

disgruntledphd2• 1 year ago

RAG is much cheaper to run.

computerex• 1 year ago

It’s significantly harder to get right, it’s a very big stepwise increase in technical complexity over in context learning/rag.

There are now some light versions of fine tuning that don’t update all the model weights but train a small adapter layer called Lora which is way more viable commercially atm in my opinion.

ijk• 1 year ago

There were initial difficulties in finetuning that made it less appealing early on, and that's snowballed a bit into having more of a focus on RAG.

Some of the issues still exist, of course:

* Finetuning takes time and compute; for one-off queries using in-context learning is vastly more efficient (i.e., look it up with RAG).

* Early results with finetuning had trouble reliably memorizing information. We've got a much better idea of how to add information to a model now, though it takes more training data.

* Full finetuning is very VRAM intensive; optimizations like LoRA were initially good at transferring style and not content. Today, LoRA content training is viable but requires training code that supports it [1].

* If you need a very specific memorized result and it's costly to get it wrong, good RAG is pretty much always going to be more efficient, since it injects the exact text in context. (Bad RAG makes the problem worse, of course).

* Finetuning requires more technical knowledge: you've got to understand the hyperparameters, avoid underfitting and overfitting, evaluate the results, etc.

* Finetuning requires more data. RAG works with a handful datapoints; finetuning requires at least three orders of magnitude more data.

* Finetuning requires extra effort to avoid forgetting what the model already knows.

* RAG works pretty well when the task that you are trying to perform is well-represented in the training data.

* RAG works when you don't have direct control over the model (i.e., API use).

* You can't finetune most of the closed models.

* Big, general models have outperformed specialized models over the past couple of years; if it doesn't work now, just wait for OpenAI to make their next model better on your particular task.

On the other hand:

* Finetuning generalizes better.

* Finetuning has more influence on token distribution.

* Finetuning is better at learning new tasks that aren't as present in the pretraining data.

* Finetuning can change the style of output (e.g., instruction training).

* When finetuning pays off, it gives you a bigger moat (no one else has that particular model).

* You control which tasks you are optimizing for, without having to wait for other companies to maybe fix your problems for you.

* You can run a much smaller, faster specialized model because it's been optimized for your tasks.

* Finetuning + RAG outperforms just RAG. Not by a lot, admittedly, but there's some advantages.

Plus the RL Training for reasoning has been demonstrating unexpectedly effective improvements on relatively small amounts of data & compute.

So there's reasons to do both, but the larger investment that finetuning requires means that RAG has generally been more popular. In general, the past couple of years have been won by the bigger models scaling fast, but with finetuning difficulty dropping there is a bit more reason to do your own finetuning.

That said, for the moment the expertise + expense + time of finetuning makes it a tough business proposition if you don't have a very well-defined task to perform, a large dataset to leverage, or other way to get an advantage over the multi-billion dollar investment in the big models.

[1] https://unsloth.ai/blog/contpretraining

omneity3• 1 year ago

RAG is infinitely more accessible and cheaper than finetuning. But it is true that finetuning is getting severely overlooked in situations where it would outperform alternatives like RAG.

onel• 1 year ago

You usually fine tune when you want to add capabilities (an output style, json output, function calling, etc). You use RAG to add knowledge

kordlessagain4• 1 year ago

Nuance is hard. Binary choices are fast, comforting, and require less thought. Certainty feels safer than ambiguity — especially in conflict, where complexity threatens identity. And in most arenas (tech, media, politics), decisive hot takes get applause. Fence-sitters get ignored.

I worked at a startup where the CEO swore up and down that real-time fine-tuning was the future — that models would continuously update with company data. It sounded cool until you remember: That’s not how LLMs work. It’s not efficient. It’s not flexible. And it’s not even necessary — we already have RAG.

Pipedreams make good pitch decks. But they break when you hit production.

It's a fucking pipedream, this. That's not how LLMs work, it's not efficient, it's not useful (we have RAG for reference augmentation), and it’s not even desirable unless you want your model overfitting on stale, internal narratives every night.

VSerge• 1 year ago

Ongoing demo of integrations with Claude by a bunch of A-list companies: Linear, Stripe, Paypal, Intercom, etc.. It's live now on: https://www.youtube.com/watch?v=njBGqr-BU54

In case the above link doesn't work later on, the page for this demo day is here: https://demo-day.mcp.cloudflare.com/

mkagenius2• 1 year ago

are people really doing this mcp thing, yikes. Tomorrow, let me reinvent css as model context design (mcd)

warkdarrior2• 1 year ago

Do you have a better solution to give models on-demand access to data sources?

mkagenius2• 1 year ago

you mean other than writing an api? no

turblety• 1 year ago

Is there a reason they went and built some new standard, rather than just using a http api?

knowaveragejoe2• 1 year ago

You can use either HTTP or stdio.

imbnwa• 1 year ago

Feel like middle management is gonna go well before engineers do with LLM rate of advancement

DebtDeflation• 1 year ago

That started awhile ago. Google "the great flattening".

6stringmerc• 1 year ago

Feed Claude the data willingly to learn more about human behavior they can’t scrape or obtain otherwise without consent? Hard pass. I’m not telling any AI any more about what it means to be a creative person because training it how to suffer will only further hurt my job prospects. Nice try, no dice.

n_ary2• 1 year ago

Is this the beginning of the apps for everything era and finally the SaaS for your LLM begins? Initially we had internet but value came when instead of installed apps, webapps arrived to become SaaS. Now if LLMs can use specific remote MCP which is another SaaS for your LLM, the remote MCP powered service can charge a subscription to do wonderful things and voila! Let the new golden age of SaaS for LLMs begin and the old fad(replace job XYZ with AI) die already.

throwaway7783• 1 year ago

MCP is yet another interface for an existing SaaS (like UI and APIs), but now magically "agent enabled". And $$$ of course

clvx• 1 year ago

I'm more excited I can run now a custom site, hook an MCP for it, and have all the cool intelligence I had to pay for SaaS without having to integrate to them plus govern my data, it's a massive win. I just see AI assistant coding replicating current SaaS services that I can run internally. If my shop was a specific stack, I could aim to have all my supporting apps in that specific stack using AI assistant coding, simplifying operations, and being able to hook up MCP's to get intelligence from all of them.

Truly, OSS should be more interesting in the next decade for this alone.

heyheyhouhou• 1 year ago

We should all thank the chinese companies for releasing so many incredible open weight models. I hope they keep doing it, I dont want to rely on OpenAI, Anthropic or Google for all my future computer interactions.

naravara• 1 year ago

On one hand, yes this is very cool for a whole host of personal uses. On the other hand giving any company this level of access to as many different personal data sources as are out there scares the shit out of me.

I’d feel a lot better if we had something resembling a comprehensive data privacy law in the United States because I don’t want it to basically be the Wild West for anyone handling whatever personal info doesn’t get covered under HIPAA.

falcor842• 1 year ago

Absolutely agreed, but just wanted to mention that it's essentially the same level of access you would give to Zapier, which is one of their top examples of MCP integrations.

n_ary2• 1 year ago

It took many years for online tracking, iframes, sticky cookies and cambridge analytics before things like GDPR came into existence. We have to similarly wait a few years before similar major leaks happen through LLM pipelines/integrations. Sadly, that is the reality we live with.

OtherShrezzing• 1 year ago

I'd love a _tip jar_ MCP, where the LLM vendor can automatically tip my website for using its content/feature/service in a query's response. Even if the amount is absolutely minuscule, in aggregate, this might make up for ad revenue losses.

fredoliveira• 1 year ago

Not that exactly, but I just saw this on twitter a few minutes ago from Stripe: https://x.com/jeff_weinstein/status/1918029261430255626

insin• 1 year ago

It's perfect, nobody will have time to care about how many 9s your service has because the nondeterministic failure mode now sitting slap-bang in the middle is their problem!

Manfred• 1 year ago

Imagine dynamic subscription rates based on vibes where you won't even notice price hikes because not even the supplier can explain what they are.

donmcronald• 1 year ago

Now if LLMs can use specific remote MCP which is another SaaS for your LLM, the remote MCP powered service can charge a subscription to do wonderful things and voila!

I've always worked under the assumption the best employees make themselves replaceable via well defined processes and high quality documentation. I have such a hard time understanding why there's so much willingness to integrate irreplaceable SaaS solutions into business processes.

I haven't used AI a ton, but everything I've done has focused on owning my own context, config, etc.. How much are people going to be willing to pay if someone else owns 10+ years of their AI context?

Am I crazy or is owning the context massively valuable?

brumar• 1 year ago

Hello fellow context owner. I like my modules with their context.sh at their root level. If crafted with care, magic happens. Reciprocally, when AI derails, it's most often due to bad context management and fixed by improving it.

drivingmenuts• 1 year ago

Is each Claude instance a separate individual or is a shared AI? Because I'm not sure I would want an AI that learned about my confidential business information sharing that with anyone else, without my express permission.

This does not sound like it would be learning general information helpful across an industry, but specific, actionable information.

If not available now, is that something that AI vendors are working toward? If so, what is to keep them from using that knowledge to benefit themselves or others of their choosing, rather than the people they are learning from?

While people understand ethics, morals and legality (and ignore them), that does not seem like something that an AI understands in a way that might give them pause before doing an action.

zoogeny4• 1 year ago

I'm curious what kind of research people are doing that takes 45 minutes of LLM time. Is this a poke at the McKinsey consultant domain?

Perhaps I am just frivolous with my own time, but I tend to use LLMs in a more iterative way for research. I get partial answers, probe for more information, direct the attention of the LLM away from areas I am familiar and towards areas I am less familiar. I feel if I just let it loose for 45 minutes it would spend too much time on areas I do not find valuable.

This seems more like a play for "replacement" rather than "augmentation". Although, I suppose if I had infinite wealth, I could kick of 10+ research agents each taking 45 minutes and then review their output as it became available, then kick off round 2, etc. That is, I could do my process but instead of interactively I could do it asynchronously.

throwup2382• 1 year ago

That iterative research process is exactly how I use Google Deep Research since it has a 20/day rate limit. Research a problem, notice some off hand assumption or remark the report made, and fire off another research run asking about it. It depends on what you work on; in my use case I often have to do hours of research for 30 minutes of work like when integrating a bunch of different vendors’ APIs or pouring over datasheets for EE, so it’s worth firing off research and then working on something else for 10-20 minutes (it helps that the Gemini app fires off a push notification when the report is done - Anthropic please do this! Even for requests made from the web app).

As for long research times, one thing I’ve been using it for is historical research on old books. Gemini DeepResearch was the first one able to properly explain the nuances of identifying a chimeral first edition Origin of Species after taking half an hour and reading 400 sources. It went into all the important details like spelling errors and the properties of chimeral FY2** copies found in various libraries around the world.

abhisek2• 1 year ago

Where is Skynet and when is judgement day?

52-6F-62• 1 year ago

1. Publishing advertisements all over the place. 2. Some Tuesday

pton_xd• 1 year ago

"To start, you can choose from Integrations for 10 popular services, including Atlassian’s Jira and Confluence, Zapier, Cloudflare, Intercom, Asana, Square, Sentry, PayPal, Linear, and Plaid. ... Each integration drastically expands what Claude can do."

Give us an LLM with better reasoning capabilities, please! All this other stuff just feels like a distraction.

Centigonal• 1 year ago

Building integrations is a more predictable way of developing a smaller competitive advantage versus research. I think most of the leading AI companies are adopting a multi-arm strategy of research + product/ecosystem development to balance their risks.

atonse7• 1 year ago

I disagree. They can walk and chew gum, do both things at once. And this practical stuff is very important.

I've been using the Atlassian MCP for nearly a month now, and it's completely changed (and eliminated) the feeling of having an overwhelming backlog.

I can have it do things like "find all the tickets related to profile editing and combine them into one epic" where it works perfectly. Or "help me prioritize the 15 tickets assigned to me this sprint" and it'll actually go through and suggest "maybe you can do these two tickets first since they seem smaller, then do this big one" – i haven't hooked it up to my calendar yet.

But I'd love for it to suggest things like "do this one ticket that requires a lot of heads down time on wednesday since you don't have any meetings. I can create a block on your calendar so that nobody will schedule a meeting then"

Those are all superhuman things that can be done with MCP and a smart model.

I've defined rules in cursor that say "when I ask you to mark something ready for test, change the status and assign it to <x person>, and leave a comment summarizing the changes"

If you look at my JIRA comments now, you'd wonder how I had so much time to write such thorough comments. I don't, Cursor and whatever model is doing it for me.

It's been an absolute game changer. MCP is going to be what the App store was to mobile. Yes you can get by without it, but actually hooking into all your daily tool is when this stuff gets insanely valuable in a practical sense.

OJFord3• 1 year ago

If you look at my JIRA comments now, you'd wonder how I had so much time to write such thorough comments. I don't, Cursor and whatever model is doing it for me.

How do your colleagues feel about it?

zoogeny4• 1 year ago

Honestly, that backlog management idea is probably the first time an MCP actually sounded appealing to me.

I'm not in that world at the moment, but I've been the lead on several projects where the backlog has became a dumping ground of years of neglect. You end up with this tiered backlog thing where one level of backlog gets too big so you create a second tier of backlog for the stuff you are actually going to work on. Pretty soon you end up with duplicates in the second tier backlog for items already in the base level backlog since no one even looks at that old backlog anymore.

I've done a lot of tidy up myself when I inherit this kind of mess, just closing tickets we definitely will never get to, de-duping, adding context when available, grouping into epics, tagging with relevant "tech-debt", "security", "bug", "automation", etc. But when there are 100s of tickets it is a slog. Having an LLM do this makes so much sense.

organsnyder• 1 year ago

I have Claude hooked up to our project management system, GitHub, and my calendar (among other things). It's already proving extremely useful for various project management tasks.

edaemon• 1 year ago

Lots of reported security issues with MCP servers seemed to be mitigated by their local-only setup. These MCP implementations are remotely accessible, do they address security differently?

paulgb• 1 year ago

Largely, yes -- one of the big issues with using other people's random MCP servers is that they are run by default as a system process, even if they only need to speak over an API. Remote MCP mitigates this by not running any untrusted code locally.

What it _doesn't_ seem to yet mitigate is prompt injection attacks, where a tool call description of one tool convinces the model to do something it shouldn't (like send sensitive data to a server owned by the attacker.) I think these concerns are a little bit overblown though; things like pypi and the Chrome Extension store scare me more and it doesn't stop them from mostly working.

zoogeny4• 1 year ago

They offhand mention OAuth integration in their discussion of Cloudflare integrated solutions. I can't see how that would be any less secure than any other OAuth protected API offering.

Nijikokun• 1 year ago

context windows are too small and conversely larger windows are not accurate enough its annoying

indigodaddy• 1 year ago

So any chat to Claude will now just auto-activate web search to be included? What if I try to use it just as a search engine exclusively? Also will proxies like Openrouter have access to the web search capabilities?

gianpaj• 1 year ago

Web search is now globally available to all Claude.ai paid plans.

surfingdino• 1 year ago

I don't know why web search is such a big deal. You can implement it with any LLM that offers an API and function calling.

tene80i• 1 year ago

Do you think most people know how to do that, or even what it means? The market is larger than just software engineers.

ChicagoDave• 1 year ago

There is targeted value in integrations, but everything still leads back to larger context windows.

I love MCP (it’s way better than plain Claude) but even that runs into context walls.

davee5• 1 year ago

I'm quite struck by the title of this announcement. The box being drawn around "your world" shows how narrow the AI builder's window into reality tends to be.

a new way to connect your apps and tools to Claude. We're also expanding... with an advanced mode that searches the web.

The notion of software eating the world, and AI accelerating that trend, always seems to forget that The World is a vast thing, a physical thing, a thing that by its very nature can never be fully consumed by the relentless expansion of our digital experiences. Your worldview /= the world.

The cynic would suggest that the teams that build these tools should go touch grass, but I think that misses the mark. The real indictment is of the sort of thinking that improvements to digital tools [intelligences?] in and of themselves can constitute truly substantial and far reaching changes.

The reach of any digital substrate inherently limited, and this post unintentionally lays that bare. And while I hear accelerationists invoking "robots" as the means for digital agents to expand their potent impact deeper into the real world I suggest this is the retort of those who spend all day in apps, tools, and the web. The impacts and potential of AI is indeed enormous, but some perspective remains warranted and occasional injections of humility and context would probably do these teams some good.

dang• 1 year ago

(Just for context: we've since changed the title above. Corporate press release titles are rarely a good fit for HN and we usually change them.

https://hn.algolia.com/?dateRange=all&page=0&prefix=true&sor...)

atonse7• 1 year ago

I think with MCPs and related tech, if Apple just internally went back to the drawing board and integrated the concept of MCPs directly into iOS (via the "Apple Intelligence" umbrella) and seamlessly integrated it into the App Store and apps, they will win the mobile race for this.

Being Apple, they would have to come up with something novel like they did with push (where you have _one_ OS process running that delegates to apps rather than every app trying to handle push themselves) rather than having 20 MCP servers running. But I think if they did this properly, it would be so amazing.

I hope Apple is really re-thinking their absolutely comical start with AI. I hope they regroup and hit it out of the park (like how Google initially stumbled with Bard, but are now hitting it out of the park with Gemini)

mattlondon2• 1 year ago

Do you really think Apple can catch up with and then surpass all these SOTA AI labs?

They bet big and got distracted on VR. It was obviously the wrong choice at the time, and even more so now. They're going to have to abandon all that VR crap and pivot hard to AI to try and catch up. I think the more likely case is they can't catch up now and will just have to end up licensing Gemini from Google/Google paying them to use Gemini as the default AI.

atonse7• 1 year ago

No I’m not saying Apple even has to build their own model. I’m saying Apple can build a stellar _product_ experience around it.

As others have pointed out, if that’s what App Intents are, have they started to integrate this as part of Apple Intelligence?

_pdp_• 1 year ago

Apple already has the equivalent of MCP. https://developer.apple.com/documentation/appintents.

bloomca• 1 year ago

That's just App Intents. I don't think they lack data at this point, they just struggle how to use that data on the OS level

cruffle_duffle3• 1 year ago

The video demos never really showed the auth “story” but I assume that there is some oauth step to connect Claude with your MCP service, right?

belter• 1 year ago

All these integrations are likely to cause a massive security leak sooner or later.

OJFord3• 1 year ago

Where's the permissioning, the data protection?

People will say 'aaah ad company' (me too sometimes) but I'd honestly trust a Google AI tool with this way more. Not just because it already has access to my Google Workspace obviously, but just because it's a huge established tech firm with decades of experience in trying not to lose (or have taken) user data.

Even if they get the permissions right and it can only read my stuff if I'm just asking it to 'research', now Anthropic has all that and a target on their backs. And I don't even know what 'all that' is, whatever it explored deeming it maybe useful.

Maybe I'm just transitioning into old guy not savvy with latest tech, but I just can't trust any of this 'go off and do whatever seems correct or helpful with access to my filesystem/Google account/codebase/terminal' stuff.

I like chat-only (well, +web) interactions where I control the input and taking the output, but even that is not an experience that gives me any confidence in giving uncontrolled access to stuff and it always doing something correct and reasonable. It's often confidently incorrect too! I wouldn't give an intern free reign in my shell either!

joshwarwick152• 1 year ago

Permissoning: OAuth Data protection: Local LLMs

weinzierl• 1 year ago

If you do not enable "Web Search" are you guaranteed it does not access the web anyway?

Sometimes I want a pure model answer and I used to use Claude for that. For research tasks I preferred ChatGPT, but I found that you cannot reliably deny it web access. If you are asking it a research question, I am pretty sure it uses web search, even when "Search" and "Deep Research" are off.

rafram• 1 year ago

Oh no, remote MCP servers. Security was nice while it lasted!

rvz2• 1 year ago

This is a fantastic time to get into the security space and trick all these LLMs into leaking sensitive data and make a lot of money out of that.

MCP is a flawed spec and quite frankly a scam.

knowaveragejoe2• 1 year ago

What makes a remotely hosted MCP server less secure? The alternative, and what most of MCP consists of at the moment, is essentially running arbitrary code on your machine, as your user, and hooking this up to an LLM.

rvz2• 1 year ago

Can't wait for the first security incident relating to the fundamentally flawed MCP specification which an LLM will inadvertently be tricked to leak sensitive data.

Increasing the amount of "connections" to the LLM increases the risk in a leak and it gives your more rope to hang yourself with when at least one connection becomes problematic.

Now is a great time to be a LLM security consultant.

dimgl• 1 year ago

This is great, but can you fix Claude 3.7 and make it more like 3.5? I'm seriously disappointed with 3.7. It seems to be performing significantly worse for me on all tasks.

Even my wife, who normally used Claude to create interesting recipes to bake cookies, has noticed a huge downgrade in 3.7.

t0lo• 1 year ago

3.7 seems to be way more filler and ambiguity and less insights for me.

bjornsing2• 1 year ago

The strategic business dynamic here is very interesting. We used to have "GPT-wrapper SaaS". I guess what we're about to see now is the opposite: "SaaS/MCP-wrapper GPTs".

jimbokun3• 1 year ago

The GPT wrappers were always going to be subsumed by improvements to the models themselves.

LLMs wrapping the services makes more sense, as the data stored in those services adds a lot of value to off the shelf LLMs.

bjornsing2• 1 year ago

I think I agree. There’s a lot of utility in a single LLM that can talk to many SaaS and integrate them. Feels like a better path forward than a separate LLM inside every SaaS.

hdjjhhvvhga• 1 year ago

The people who connect a LLM to their Paypal and CLoudflare accounts perfectly deserve the consequences, both positive and negative.

conroy• 1 year ago

Remote MCP servers are still in a strange space. Anthropic updated the MCP spec about a month ago with a new Streamable HTTP transport, but it doesn't appear that Claude supports that transport yet.

When I hooked up our remote MCP server, Claude sends a GET request to the endpoint. According to the spec, clients that want to support both transports should first attempt to POST an InitializeRequest to the server URL. If that returns a 4xx, it should then assume the SSE integration.

kordlessagain4• 1 year ago

Claude Desktop doesn't support resources without directly importing them and now they've taken the button away for that and tools so I have to build the status of them into a tool so I could see what was loading and what wasn't.

Here's my tool for Desktop: https://github.com/kordless/EvolveMCP

gonzan• 1 year ago

So there are going to be companies built on just an MCP server I guess, wonder what the first big one will be, just a matter of time I think

worldsayshi2• 1 year ago

Is it just me that would like to see more of confirmations before making opaque changes to remote systems?

I might not dare to add an integration if it can potentially add a bunch of stuff to the backing systems without my approval. Confirmations and review should be part of the protocol.

sepositus• 1 year ago

Yeah, this was my first thought. I was watching the video of it creating all of these Jira tickets just thinking in my head: "I hope it just did all that correctly." I think the level of patience with my team would be very low if I started running an LLM that accidentally deleted a bunch of really important tickets.

worldsayshi2• 1 year ago

Yeah. Feels like it's breaking some fundamental UX principle. If an action is going to make any significant change make sure that it fulfills at least one of these:

1. Can be rollbacked/undone

2. Clearly states exactly what it's going to do in a reviewable way

If those aren't fulfilled you're going to end up with users that are afraid of using your app.

todsacerdoti• 1 year ago

Check out 2500+ MCP servers at https://mcp.pipedream.com

the_clarence2• 1 year ago

Been playing with MCP in the last few days and it's basically a more streamlined way to define tools/function calls.

That + the agent SDK of openAI makes creating agentic flow so easy.

On the other hand you're kinda forced to run these tools / MCP servers in their own process which makes no sense to me.

nilslice2• 1 year ago

you might like mcp.run, a tool management platform we're working on... totally agree running a process per tool, with all kinds of permissions is nonsensical - and the move to "remote MCP" is a good one!

but, we're taking it a step (or two) further, enabling you to dynamically build up a MCP server from other servers managed in your account with us.

try it out, or let me get you a demo! this goes for any casual comment readers too ;)

https://cal.com/team/dylibso/mcp.run-demo

the_clarence2• 1 year ago

I meant I wanted to run them synchronously in the same process :)

kostas_f3• 1 year ago

Anthropic's strategy seems to go towards "AI as universal glue". They want to tie Claude into all the tools teams already live in (Jira, Confluence, Zapier, etc.). That's a smart move for enterprise adoption, but it also feels like they're compensating for a plateau in core model capabilities.

Both OpenAI and Google continue to push the frontier on reasoning, multimodality, and efficiency whereas Claude's recent releases have felt more iterative. I'd love to see Anthropic push into model research again.

bl4ckneon• 1 year ago

I am sure they are already doing that. To think that an AI researcher is doing essentially api integration work is a bit silly. Multiple efforts can happen at the same time

kostas_f3• 1 year ago

They certainly have internal research efforts underway, but I'm talking about what’s actually been released to end users via the Claude app or API. Their latest public Sonnet release 3.7 (feb 2025) felt pretty incremental compared to Sonnet 3.5 (june 2024), especially when you compare them to OpenAI and Google released models. In terms of the models you can integrate today, Anthropic hasn’t quite kept pace on either reasoning performance or cost efficiency.

freewizard• 1 year ago

I would expect Slack do this. Maybe Slack and Claude should merge one day, given MS and Google has their own core models.

tjsk• 1 year ago

Slack is owned by Salesforce which is doing its own Agentforce stuff

kostas_f3• 1 year ago

Anthropic is now too expensive to be acquired. Only Amazon could be a potential buyer, given that out of the 3 big cloud providers, it's the only one without their own model offering.

kordlessagain4• 1 year ago

What they are doing is taking the model and elevating it to the level of attention controller in the conversation. It can run tools, spout inferences, etc. If they can control the UI in the CLIENT, they win. If they don't, they have to rely on someone putting their API integration into another project.

deanc• 1 year ago

I find it absolutely astonishing that Atlassian hasn’t yet provided an LLM for confluence instances and instead a third party is required. The sheer scale of documentation and information I’ve seen at some organisations I’ve worked with is overwhelming. This would be a killer feature. I do not recommend confluence to my clients simply because the search is so appalling .

Keyword search is such a naive approach to information discovery and information sharing - and renders confluence in big orgs useless. Being able to discuss and ask questions is a more natural way of unpacking problems.

artur_makly2• 1 year ago

on their announcement page they wrote " In addition to these updates, we're making WEB SEARCH available globally for all Claude users on paid plans."

So I tested a basic prompt:

1. go to : SOME URL

2. copy all the content found VERBATIM, and show me all that content as markdown here.

Result : it FAILED miserably with a few basic html pages - it simply is not loading all the page content in its internal browser.

What worked well: - Gemini 2.5Pro (Experimental) - GPT 4o-mini // - Gemini 2.0 Flash ( not verbatim but summarized )

meander_water2• 1 year ago

Looks like this is possible due to the relatively recent addition of OAuth2.1 to the MCP spec [0] to allow secure comms to remote servers.

However, there's a major concern that server hosters are on the hook to implement authorization. Ongoing discussion here [1].

[0] https://modelcontextprotocol.io/specification/2025-03-26

[1] https://github.com/modelcontextprotocol/modelcontextprotocol...

dmarble• 1 year ago

Direct link to the spec page on authorization: https://modelcontextprotocol.io/specification/2025-03-26/bas...

Source: https://github.com/modelcontextprotocol/modelcontextprotocol...

marifjeren3• 1 year ago

That github issue is closed but:

major concern that server hosters are on the hook to implement authorization

Doesn't it make perfect sense for server hosters to implement that? If Claude wants access to my Jira instance on my behalf, and Jira hosts a remote MCP server that aids in exposing the resources I own, isn't it obvious Jira should be responsible for authorization?

How else would they do it?

cruffle_duffle3• 1 year ago

The authorization server and resource server can be separate entities. Meaning that jira instance can validate the token but not be the one issuing it or handling credentials.

halter73• 1 year ago

That github issue is closed because it's been mostly completed. As of https://github.com/modelcontextprotocol/modelcontextprotocol..., the latest draft specification does not require the resource server to act as or poxy to the IdP. It just hasn't made its way to a ratified spec yet, but SDKs are already implementing the draft.

bdd_pomerium• 1 year ago

This is very cool. Integrations look slick. Folks are understandably hyped—the potential for agents doing "deep research-style" work across broad data sources is real.

But the thread's security concerns—permissions, data protection, trust—are dead on. There is also a major authN/Z gap, especially for orgs that want MCP to access internal tools, not just curated SaaS.

Pushing complex auth logic (OAuth scopes, policy rules) into every MCP tool feels backwards.

* Access-control sprawl. Each tool reinvents security. Audits get messy fast.

* Static scopes vs. agent drift. Agents chain calls in ways no upfront scope list can predict. We need per-call, context checks.

* Zero-Trust principles mismatch. Central policy enforcement is the point. Fragmenting it kills visibility and consistency.

We already see the cost of fragmented auth: supply-chain hits and credential reuse blowing up multiple tenants. Agents only raise the stakes.

I think a better path (and in one in full disclosure, we're actively working on at Pomerium ) is to have:

* One single access point in front of all MCP resources.

* Single sign-on once, then short-lived signed claims flow downstream..

* AuthN separated from AuthZ with a centralized policy engine that evaluates every request, deny-by-default. Evaluation in both directions with hooks for DLP.

* Unified management, telemetry, audit log and policy surface.

I’m really excited about what MCP is putting us in the direction of being able to do with agents.

But without a higher level way to secure and manage the access, I’m afraid we’ll spend years patching holes tool by tool.

tkgally• 1 year ago

For the past couple of months, I’ve been running occasional side-by-side tests of the deep research products from OpenAI, Google, Perplexity, DeepSeek, and others. Ever since Google upgraded its deep research model to Gemini 2.5 Pro Experimental, it has been the best for the tasks I give them, followed closely by OpenAI. The others were far behind.

I ran two of the same prompts just now through Anthropic’s new Advanced Research. The results for it and for ChatGPT and Gemini appear below. Opinions might vary, but for my purposes Gemini is still the best. Claude’s responses were too short and simple and they didn’t follow the prompt as closely as I would have liked.

Writing conventions in Japanese and English

https://claude.ai/public/artifacts/c883a9a5-7069-419b-808d-0...

https://docs.google.com/document/d/1V8Ae7xCkPNykhbfZuJnPtCMH...

https://chatgpt.com/share/680da37d-17e4-8011-b331-6d4f3f5ca7...

Overview of an industry in Japan

https://claude.ai/public/artifacts/ba88d1cb-57a0-4444-8668-e...

https://docs.google.com/document/d/1j1O-8bFP_M-vqJpCzDeBLJa3...

https://chatgpt.com/share/680da9b4-8b38-8011-8fb4-3d0a4ddcf7...

The second task, by the way, is just a hypothetical case. Though I have worked as a translator in Japan for many years, I am not the person described in the prompt.

noisy_boy• 1 year ago

What is the best stack/platform to get started with MCP? I'm talking in terms of ergonomics, features and popularity.

jngiam1• 1 year ago

This is awesome. We implemented a MCP client that's fully compatible with the new remote MCP specs, support OAuth and all. It's really smooth and I think paves the way for AI to work with tools. https://lutra.ai/mcp

jes5199• 1 year ago

the MCP spec as it stands today is pretty half-baked. It’s pretty clear that the first edition was trying to emulate STDIO over HTTP, but that meant holding open a connection indefinitely. The new revision tries to solve this by letting you hold open as many connections as you want! but that makes it vague about message delivery ordering when you have multiple streams open. There even seems to be part of the spec that is logically impossible - people are wrestling with it in the GitHub issues.

which is to say: I’m not sure it actually wins, technically, over the OpenAI/OpenAPI idea from last year, which was at least easy to understand

sagarpatil• 1 year ago

Should have just called it Remote MCP. Integrations sounds very vague.

Surac• 1 year ago

I often use Claude 3.7 on programming things never done before. Even extensive search in the web brings up zero hits. I understand that this is very uncommon but my work portfolio is more science than real programming. Claude 3.7 really „thinks“ about the questions i ask. But 3.5 regularly drifts into dream mode if asked anything over it‘s training data. So if you ask for code easy found on the web you will see no difference. Try asking things not so common and you will see a difference

_1tem• 1 year ago

Finally I can do something simple that I’ve wanted to do for ages: paste in a poster image or description of an event and tell the AI to add it to my calendar.

gjohnhazel• 1 year ago

I just have it create an .ics file and open that

franze• 1 year ago

Integrations and advanced Research are now available in beta on the Max, Team, and Enterprise plans, and will soon be available on Pro.

MarkMarine• 1 year ago

The plaid integration is to let you look at your install? I was excited to see all my accounts (as a consumer) knit together and reported on by Claude. Bummer

sebstefan• 1 year ago

An AI that is capable of responding to a "How do I do X" prompt with "Hey this seems related to a ticket that was already opened on your Jira 2 months ago", or "There is a document about this in Sharepoint", it would bring me such immense value, I think I might cry.

Edit: Actually right in the tickets themselves would probably be better and not require MCP... but still

MagicMoonlight• 1 year ago

Copilot can already be setup to use sharepoint etc. And you can set it up to only respond based on internal content.

So if you ask it “who is in charge of marketing” it will read it off sharepoint instead of answering generically

elia_42• 1 year ago

Very interesting. The integration videos are great to start right away and try out the new features. The extensions of the deep reasoning capabilities are also incredible.

I think we are coming to a new automated technology ecosystem where LLMs will orchestrate many different parts of software with each other, speeding up the launch, evolution and monitoring of products.

abhisek2• 1 year ago

Looks to me another apps ecosystem coming up similar to Android or iPhone. We are probably going to see a lot of AI apps marketplaces that solve the problem of discovery, billing & integration with AI hosts like Claude Desktop.

game_the0ry2• 1 year ago

Its only a matter of time where folks write user stories and an LLM takes over for the first draft, then iterate from there.

Btw, that speaks to how important it is to get clear business requirements for work.

clintonb• 1 year ago

Greptile (https://www.greptile.com/) tries to do that, at least for bug tickets. I recall being annoyed by its suggestions (posted as Linear comments).

dakshgupta2• 1 year ago

Co-founder of Greptile - that was a bad feature that we since deprecated to focus entirely on AI code reviews

ausbah• 1 year ago

usability like this seems to be a big nail through oss llm usage

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