Show HN: In Memoria – AI memory layer for persistent context in coding tools (opens in new tab)

A couple weeks ago I shared In Memoria, an MCP server that gives AI coding assistants persistent memory. The basic problem is that tools like Claude and Copilot forget everything between sessions (I now call this 'Session Amnesia'), so you end up repeating your codebase context and preferences every time.

In Memoria runs locally (npx in-memoria server) and learns your naming conventions, architectural patterns, and project structure by parsing your code with tree-sitter. It supports 12 languages now, including TypeScript, Python, Rust, Go, and C++.

The AI tools connect over MCP and use that memory to give context-aware suggestions without starting fresh every session.

Would love to hear if anyone else is working on something like this or has feedback on using pattern learning versus explicit configs.

Repo: https://github.com/pi22by7/In-Memoria