📡 MCP Radar

richarvey/OmniMem

Self-hosted semantic memory for AI Agents. Persistent sessions, experience scoring, and a graveyard for dead ends, backed by knowledge acquired from the RSS you read and stored in a Valkey vector sear

9 stars
0 forks
Python
momentum ▲ 18.0
created 2026-07-14
on radar since 2026-07-17
star trend 3 → 9 since 2026-07-17
aiclaudecodexmcpmemoryself-hostedselfhosted-aisemantic-searchvalkey
View on GitHub ↗Homepage ↗

About OmniMem

\ Development happens on Codeberg (https://codeberg.org/richarvey/omnimem) — issues and PRs there please. ---

[!WARNING] SSE transport is deprecated. OmniMem 3.10 defaults to SSE but now supports Streamable HTTP via MCPTRANSPORT=http. SSE will be removed in a future release. To migrate: set MCPTRANSPORT=http in your .env and update your client config to use "type": "http" with URL .../mcp instead of .../sse. See the connection guides for updated examples.

Streamable HTTP support is a community contribution from @timstoop — thanks!

Every Claude Code session starts from zero. No memory of your project. No memory of what failed last week. No memory that you spent three hours last Tuesday discovering why onnxruntime explodes on Alpine before finding something that actually works.

So you explain the project again. Claude suggests the same broken library again. Same alarm. Same song. You are Bill Murray and Claude is Punxsutawney.

OmniMem fixes that. It is a self-hosted MCP server that gives Claude Code persistent memory across sessions, projects, and machines. It runs on your own hardware and it is free forever.

OmniMem gives Claude Code four things it currently lacks.

Episodic memory is the decisions you made, the bugs you fixed, the patterns you discovered. The things that took real effort to learn and should not have to be re-learned every morning.

Project context is your stack, goals, and current state. Claude arrives at every session already briefed rather than starting cold.

From the project README.

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