MCP.Market

Core MCP server

by omega-memory·io.github.omega-memory/core·v0.9.3·218 stars

Persistent memory for AI coding agents. #1 on LongMemEval. Local-first.

A89/100grade A
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Safety scan
A89/100

full report

Adoption
Growing

218 stars

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If you have run it, two minutes of your experience saves the next person an afternoon.

Core 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 · 2026-09-28 · same rubric, same numbers if you re-run it

no findings
  • Code scan34 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
Overall 89/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How Core 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

Install Core in Claude Code, Cursor or VS Code

claude mcp add core -- uvx omega-memory
Add to Cursor

What the publisher says

From the Core 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 works

Claude Desktop

pip install omega-memory[server]
omega setup --client claude-desktop

This 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, codex

Library-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 process
from 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 setup

omega setup will:

  1. Create ~/.omega/ directory
  2. Download the ONNX embedding model (~90 MB) to ~/.cache/omega/models/
  3. Register omega-memory as an MCP server (Claude Code auto-detected, or specify --client)
  4. Install session hooks into ~/.claude/settings.json
  5. 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.

Core: common questions

Is Core MCP server safe?
Yes, by our scan: it is graded A (89/100). Read the Core safety report
How do I install Core?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does Core need an API key?
Not as far as the registry entry and our scan can tell: no credentials are declared or required.
Is Core maintained?
The last commit was 49 days ago (2026-09-16). The latest release is v0.9.3.
What can I use instead of Core?
Servers from other publishers that do the same job: Deja Vu MCP server, Memorix MCP server and Nautilus Compass Memory MCP server. Compare all Core alternatives.
How does Core 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). Full comparison.

Alternatives to Core

Same job from other publishers: the closest match first, then the best rated.

All Core alternatives →
  • Deja Vu
    deja-vu: local memory over the session histories of forty-three coding agents.
    A
  • Memorix
    Local-first project memory with legacy MCP and 2026 discovery compatibility.
    B
  • Nautilus Compass Memory
    Local-first long-term memory for AI agents, with byte-recomputable signed verification receipts.
    B
  • State Memory MCP
    Persistent workflow graph server tracking tasks, decisions, spatial entities, and blockers.
    A
  • Knowl
    Persistent memory for AI agents, for code, research and everyday life. Stale facts retire.
    A