ContextCore: AI Agents conversations to an MCP-queryable memory layer

by mihaitoth • 4 months ago

2 1 4 months ago

mihaitoth• 4 months ago

Hello :). This OSS product is for you (or future-you) who reached the point of wanting to tap into the ton of knowledge you have in your AI chat histories. "Hey, Agent, we have a problem with SomeClass.function, remind me what we changed in the past few months".

Product's tl;dr:

ContextCore is a local-first memory layer that ingests AI coding chats across multiple IDE assistants and machines, makes them searchable (keyword + optional semantic), and exposes them to assistants over MCP so future sessions don’t start from zero.

IMPORTANT: I emphasize local-first, as in nothing is sent to any LLM other than when you explicitly use the MCP server in the context of using an LLM. However, once you engage semantic vector search OR chat content summarization, we DO use LLMs (although you can use local ones).

ContextCore is not just “chat history storage.” It is *a developer-grade memory layer* that turns AI-assisted development from ephemeral to iterative—where prior debugging sessions, architectural decisions, refactors, and tool-call outcomes become reusable context rather than lost effort.

ContextCore: AI Agents conversations to an MCP-queryable memory layer

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