OMEGA Memory MCP server
io.github.omega-memory/omega-memory·v1.3.0·218 starsPersistent memory, coordination, and learning for AI agents. Local-first, 25 MCP tools.
218 stars416 downloads/wk
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If you have run it, two minutes of your experience saves the next person an afternoon.
OMEGA Memory tools
No tool declarations could be read from the package source. They show once the server is installed.
Public scan report
scanner v0.1.10 · 2026-09-27 · same rubric, same numbers if you re-run it
- Code scan104 source files scanned25/25
- –Live reliabilityno gateway calls yet and no remote to proben/a
- –Tool poisoningtools not inspected (local package is not executed); not countedn/a
- Auth qualitylocal package, no credentials required12/15
- Maintenancelast push 12 days ago15/15
- Maintainer identityregistry namespace matches repository owner6/10
How OMEGA Memory compares
Against every graded MCP server, from our own scans and uptime checks. Updated after each scan run.
- Safety score
- 89/100
- higher than 80% of 48,255 servers
- GitHub stars
- 218
- more than 95% of 28,688 servers
- Downloads a week
- 416
- more than 86% of 12,191 servers with a package
Install OMEGA Memory in Claude Code, Cursor or VS Code
claude mcp add omega-memory -- uvx omega-memory
What the publisher says
From the OMEGA Memory repository's README, as published. We do not edit it. Read it on GitHub
OMEGA
Cross-model memory for AI agents. Local-first. Works with Claude, GPT, Gemini, Cursor, Claw Code, and any MCP client. Your agent's brain shouldn't live on someone else's server, or be locked to one provider.
The Problem
AI coding agents are stateless. Every new session starts from zero. The "solutions" either lock you into one model provider or send your codebase context to their cloud.
- Context loss. Agents forget every decision, preference, and architectural choice between sessions. Developers spend 10-30 minutes per session re-explaining context that was already established.
- Repeated mistakes. Without learning from past sessions, agents make the same errors over and over. They don't remember what worked, what failed, or why a particular approach was chosen.
- Cloud memory = someone else's database. Services like Mem0 require API keys and send your data to their servers. When they change pricing, get acquired, or go down, your agent's accumulated intelligence disappears.
- Vendor lock-in. Anthropic's Memory Tool only works with Claude. OpenAI's memory only works with GPT. Switch models, lose your memory.
OMEGA solves this. Memory, coordination, and learning that runs entirely on your machine. Works with every major LLM and coding agent. No cloud. No API keys. No vendor lock-in.
<!-- TODO: terminal GIF showing memory recall across sessions --> <!-- mcp-name: io.github.omega-memory/omega-memory -->
Quick Install
pip install omega-memory[server] # Full install (memory + MCP server)
omega setup # Downloads model, registers MCP, installs hooks
omega doctor # Verify everything worksClaude Desktop
pip install omega-memory[server]
omega setup --client claude-desktopThis registers OMEGA as an MCP server in Claude Desktop's config. Restart Claude Desktop to activate.
Cursor, Claw Code, Windsurf, Cline, Codex
pip install omega-memory[server]
omega setup --client cursor # or: claw-code, windsurf, cline, codexLibrary-only install (no MCP server)
If you only need OMEGA as a Python library for scripts, CI/CD, or automation:
pip install omega-memory # Core only, no MCP server processfrom omega import store, query, remember
store("Always use TypeScript strict mode", "user_preference")
results = query("TypeScript preferences")This gives you the full storage and retrieval API without running an MCP server (~50 MB lighter, no background process). Hooks still work:
omega setup --hooks-only # Auto-capture + memory surfacing, no MCP server (~600MB RAM saved)From Source
git clone https://github.com/omega-memory/omega.git
cd omega
pip install -e ".[server,dev]"
omega setupomega setup will:
- Create ~/.omega/ directory
- Download the ONNX embedding model (~90 MB) to ~/.cache/omega/models/
- Register omega-memory as an MCP server (Claude Code auto-detected, or specify --client)
- Install session hooks into ~/.claude/settings.json
- Add an OMEGA block to ~/.claude/CLAUDE.md
60-Second Quickstart
OMEGA works through natural language — no API calls, no configuration. Just talk to Claude.
1. Tell Claude to remember something:
"Remember that the auth system uses JWT tokens, not session cookies"
Claude stores this as a permanent memory with semantic embeddings.
2. Close the session. Open a new one.
3. Ask about it:
"What did I decide about authentication?"
Shortened. The full README is on GitHub.
Nothing above is checked by us. What we check is on the safety report.
OMEGA Memory: common questions
- Is OMEGA Memory MCP server safe?
- Yes, by our scan: it is graded A (89/100). Read the OMEGA Memory safety report
- How do I install OMEGA Memory?
- It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
- Does OMEGA Memory need an API key?
- Not as far as the registry entry and our scan can tell: no credentials are declared or required.
- Is OMEGA Memory maintained?
- The last commit was 49 days ago (2026-09-16). The latest release is v1.3.0.
- What can I use instead of OMEGA Memory?
- Servers from other publishers that do the same job: Memorix MCP server, Nautilus Compass Memory MCP server and Honcho MCP server. Compare all OMEGA Memory alternatives.
- How does OMEGA Memory compare with other MCP servers?
- safety score 89/100 (higher than 80% of 48,255 servers); github stars 218 (more than 95% of 28,688 servers); downloads a week 416 (more than 86% of 12,191 servers with a package). Full comparison.
Alternatives to OMEGA Memory
Same job from other publishers: the closest match first, then the best rated.
MemorixLocal-first project memory with legacy MCP and 2026 discovery compatibility.not reviewedEstablishedB- Nautilus Compass MemoryLocal-first long-term memory for AI agents, with byte-recomputable signed verification receipts.not reviewedEstablishedB
- HonchoMemory that reasons: continual learning for stateful agents. Better context, fewer tokens.not reviewedEstablishedA
State Memory MCPPersistent workflow graph server tracking tasks, decisions, spatial entities, and blockers.not reviewedEstablishedA
KnowlPersistent memory for AI agents, for code, research and everyday life. Stale facts retire.not reviewedEstablishedA