OMEGA MCP Server

Local setup required. This server has to be cloned and prepared on your machine before you register it in Claude Code.
1

Set the server up locally

Run this once to clone and prepare the server before adding it to Claude Code.

Run in terminal
pip install omega-memory[server]
omega setup
2

Register it in Claude Code

After the local setup is done, run this command to point Claude Code at the built server.

Run in terminal
claude mcp add omega-memory -- node "<FULL_PATH_TO_OMEGA_MEMORY>/dist/index.js"

Replace <FULL_PATH_TO_OMEGA_MEMORY>/dist/index.js with the actual folder you prepared in step 1.

README.md

Persistent Memory for AI Coding Agents

OMEGA

AI agents that remember, coordinate, and learn. All on your machine. Your agent's brain shouldn't live on someone else's server.


The Problem

AI coding agents are stateless. Every new session starts from zero. And the "solutions" want you to 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.

OMEGA solves this. Memory, coordination, and learning that runs entirely on your machine. No cloud. No API keys. No vendor lock-in.

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
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 with Claude Code
  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?"

OMEGA surfaces the relevant memory automatically:

Found 1 relevant memory:
  [decision] "The auth system uses JWT tokens, not session cookies"
  Stored 2 days ago | accessed 3 times

That's it. Memories persist across sessions, accumulate over time, and are surfaced automatically when relevant — even if you don't explicitly ask.

Key Features

  • Memory & Learning — Stores decisions, lessons, error patterns, and preferences with semantic search. Claude recalls what matters without you re-explaining everything each session. 25 memory tools including compaction, consolidation, timeline, graph traversal, and context virtualization (checkpoint/resume).

  • Multi-Agent Coordination (omega-pro) — File and branch locking, session management, task queues with dependencies, intent broadcasting, and agent-to-agent messaging. 29 coordination tools that prevent agents from overwriting each other's work.

  • Intelligent LLM Routing (omega-pro) — Classifies tasks and routes to the optimal model. Coding → Claude Sonnet. Quick edit → Llama 8b at 1/60th the cost. 1M token context → Gemini Flash. 5 providers, 4 priority modes, sub-2ms intent classification.

  • Knowledge Base (omega-pro) — Ingest PDFs, markdown, web pages, and text files into a searchable knowledge base with semantic chunking.

  • Entity Registry (omega-pro) — Multi-entity corporate memory with relationships, hierarchies, and entity-scoped memories/profiles/documents.

  • Secure Profile (omega-pro) — AES-256 encrypted personal data storage with macOS Keychain integration.

How OMEGA Compares

Feature OMEGA Mem0 Zep Copilot Memory
Your data stays on your machine Yes No No No

Tools (2)

storeStores information or preferences into persistent memory
queryRetrieves relevant memories based on semantic search

Configuration

claude_desktop_config.json
{"mcpServers": {"omega-memory": {"command": "omega", "args": ["serve"]}}}

Try it

Remember that the auth system uses JWT tokens, not session cookies.
What did I decide about authentication in our last session?
Recall my preferred architectural patterns for React components.
List the error patterns I encountered while working on the API integration.

Frequently Asked Questions

What are the key features of OMEGA?

Persistent memory storage for AI agents that survives session restarts. Semantic search for recalling decisions, preferences, and error patterns. Local-first architecture with no cloud API keys or vendor lock-in. Automatic memory surfacing when relevant to the current task. Supports memory compaction, consolidation, and graph traversal.

What can I use OMEGA for?

Maintaining architectural context across long-term coding projects. Storing user-specific coding preferences and style guidelines. Preventing agents from repeating past mistakes by recalling failed approaches. Managing complex task dependencies and session state for multi-agent workflows.

How do I install OMEGA?

Install OMEGA by running: pip install omega-memory[server] && omega setup

What MCP clients work with OMEGA?

OMEGA works with any MCP-compatible client including Claude Desktop, Claude Code, Cursor, and other editors with MCP support.

Turn this server into reusable context

Keep OMEGA docs, env vars, and workflow notes in Conare so your agent carries them across sessions.

Need the old visual installer? Open Conare IDE.
Open Conare