omega-memory — Persistent Memory for Coding Agents

Main

• Use the server+hooks path if you want ambient memory: setup wires MCP + session hooks so recall happens at session start, not only when you remember to query.

• Start by storing explicit decisions (architecture, style, constraints), then rely on semantic query when a new session begins to keep continuity.

• If you only need a library (no server), use the README’s core-only install — but expect fewer integrations than the MCP server flow.

Source-backed notes

• README Quick Install shows pip install omega-memory[server] followed by omega setup and omega doctor.
• README states omega setup downloads an ONNX embedding model (~90MB) and registers an MCP server for supported clients.
• README lists a memory-tool table (25 tools) and documents a CLI section for setup/doctor/status.

FAQ

• Does it send data to the cloud?: README frames it as local-first; any network traffic comes from your LLM provider, not the memory store itself.
• Can I use it without MCP?: Yes — README shows a library-only install, but integrations are strongest with the MCP server flow.
• What’s a good first memory?: Store one durable rule (e.g., linting or architecture constraint) and verify it’s recalled on the next session start.