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OMEGA Memory

omega-memory/omega-memory
15826 toolsSTDIOregistry active
Summary

If you're tired of re-explaining your codebase architecture every time you start a new Claude session, this one's for you. Runs entirely local as an MCP server with 25 memory tools including `omega_store` for persisting decisions and preferences, `omega_query` for semantic search across past sessions, and automatic context surfacing when relevant. Works with Claude Desktop, Cursor, and any MCP client without sending data to external APIs. Uses ONNX embeddings on-device and stores everything in a local SQLite database. The pro version adds multi-agent coordination with file locking and task queues, plus LLM routing that picks the cheapest model for each task type. Install with pip, run `omega setup`, and memories persist across sessions without configuration.

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Tools

Public tool metadata for what this MCP can expose to an agent.

26 tools
omega_storeStore a memory with optional type and metadata. Use when the user says 'remember this' or for programmatic capture (decisions, lessons, errors). Defaults to type 'memory' if event_type is omitted.9 params

Store a memory with optional type and metadata. Use when the user says 'remember this' or for programmatic capture (decisions, lessons, errors). Defaults to type 'memory' if event_type is omitted.

Parameters* required
textstring
Alias for content — use either content or text
contentstring
Memory content (also accepts 'text' as alias)
projectstring
metadataobject
Additional metadata
priorityinteger
Memory priority 1-5 (5=highest). Auto-set from event type if omitted.
entity_idstring
Scope this memory to an entity (e.g., 'acme'). Omit for unscoped.
agent_typestring
Agent type for sub-agent memory scoping (e.g., 'code-reviewer', 'test-runner').
event_typestring
Type: memory (default), session_summary, task_completion, error_pattern, lesson_learned, decision, user_preference
session_idstring
omega_querySearch memories — semantic (default) or exact phrase match. Use mode='phrase' for literal substring search (error messages, specific strings).13 params

Search memories — semantic (default) or exact phrase match. Use mode='phrase' for literal substring search (error messages, specific strings).

Parameters* required
modestring
Search mode: 'semantic' (default) for meaning-based search, 'phrase' for exact substring matchone of semantic · phrase
limitinteger
default: 10
querystring
Search query (or exact phrase when mode='phrase')
projectstring
entity_idstring
Filter results to a specific entity (e.g., 'acme'). Omit for all.
agent_typestring
Filter results to a specific agent type (e.g., 'code-reviewer'). Omit for all.
event_typestring
Filter by event type
session_idstring
filter_tagsarray
Hard filter — only return memories containing ALL specified tags (AND logic)
context_filestring
Current file being edited (boosts results relevant to this file's context)
context_tagsarray
Current context tags like language, tools (boosts matching results)
case_sensitiveboolean
Case-sensitive search (only used with mode='phrase', default false)default: false
temporal_rangearray
Optional [start_iso, end_iso] date range filter. Auto-inferred from query text if omitted.
omega_welcomeGet a session welcome briefing with recent relevant memories and user profile.2 params

Get a session welcome briefing with recent relevant memories and user profile.

Parameters* required
projectstring
session_idstring
omega_profileRead or update the user profile. Returns the profile by default. If 'update' dict is provided, merges those fields into the profile and saves.1 params

Read or update the user profile. Returns the profile by default. If 'update' dict is provided, merges those fields into the profile and saves.

Parameters* required
updateobject
Profile fields to save (merged with existing). Omit to read profile.
omega_delete_memoryDelete a specific memory by its ID.1 params

Delete a specific memory by its ID.

Parameters* required
memory_idstring
The memory ID to delete
omega_edit_memoryEdit the content of a specific memory.2 params

Edit the content of a specific memory.

Parameters* required
memory_idstring
The memory ID to edit
new_contentstring
New content for the memory
omega_list_preferencesList all stored user preferences.

List all stored user preferences.

No parameter schema in public metadata yet.

omega_healthDetailed health check with memory usage, node counts, cache stats, warnings, and recommendations.3 params

Detailed health check with memory usage, node counts, cache stats, warnings, and recommendations.

Parameters* required
warn_mbnumber
Memory warning threshold in MB (default 350)default: 350
max_nodesinteger
Maximum expected nodes (default 10000)default: 10000
critical_mbnumber
Memory critical threshold in MB (default 800)default: 800
omega_backupExport or import memories for backup/restore. Default mode is export.3 params

Export or import memories for backup/restore. Default mode is export.

Parameters* required
modestring
Operation mode: 'export' (default) or 'import'default: export
filepathstring
File path for export or import
clear_existingboolean
Clear current data before import (default true, only used in import mode)default: true
omega_lessonsRetrieve cross-session or cross-project lessons learned, ranked by verification count and access frequency.7 params

Retrieve cross-session or cross-project lessons learned, ranked by verification count and access frequency.

Parameters* required
taskstring
Optional task description for relevance filtering
limitinteger
Max lessons to return (default 5)default: 5
agent_typestring
Filter lessons to a specific agent type (e.g., 'code-reviewer'). Omit for all.
project_pathstring
Optional project scope
cross_projectboolean
If true, search across all projects (default false)default: false
exclude_projectstring
Project path to exclude (only used with cross_project=true)
exclude_sessionstring
Session ID to exclude
omega_feedbackRecord feedback on a surfaced memory (helpful, unhelpful, outdated). Improves future surfacing quality.3 params

Record feedback on a surfaced memory (helpful, unhelpful, outdated). Improves future surfacing quality.

Parameters* required
ratingstring
One of: helpful, unhelpful, outdated
reasonstring
Optional explanation
memory_idstring
The memory node ID to rate
omega_clear_sessionClear all memories for a specific session. Use for cleanup after test sessions.1 params

Clear all memories for a specific session. Use for cleanup after test sessions.

Parameters* required
session_idstring
The session ID to purge
omega_similarFind memories similar to a given memory. Use for discovering related context.2 params

Find memories similar to a given memory. Use for discovering related context.

Parameters* required
limitinteger
Max results (default 5)default: 5
memory_idstring
The memory node ID to find similar memories for
omega_timelineShow memory timeline grouped by day. Use to see what was captured recently.2 params

Show memory timeline grouped by day. Use to see what was captured recently.

Parameters* required
daysinteger
Number of days to look back (default 7)default: 7
limit_per_dayinteger
Max memories per day (default 10)default: 10
omega_consolidateRun memory consolidation: prune stale low-value memories, cap session summaries, clean orphaned edges. Returns a report.2 params

Run memory consolidation: prune stale low-value memories, cap session summaries, clean orphaned edges. Returns a report.

Parameters* required
prune_daysinteger
Prune zero-access memories older than N days (default 30)default: 30
max_summariesinteger
Max session summaries to keep (default 50)default: 50
omega_traverseTraverse the memory relationship graph from a starting memory. Shows all connected memories within N hops, useful for understanding context chains and discovering related knowledge clusters.3 params

Traverse the memory relationship graph from a starting memory. Shows all connected memories within N hops, useful for understanding context chains and discovering related knowledge clusters.

Parameters* required
max_hopsinteger
Maximum traversal depth (1-5, default 2)default: 2
memory_idstring
The starting memory node ID
min_weightnumber
Minimum edge weight to follow (0.0-1.0, default 0.0)default: 0
omega_compactCompact related memories into consolidated knowledge nodes. Finds clusters of similar memories (same event type, high overlap) and creates summary nodes, marking originals as superseded. Reduces noise while preserving knowledge.4 params

Compact related memories into consolidated knowledge nodes. Finds clusters of similar memories (same event type, high overlap) and creates summary nodes, marking originals as superseded. Reduces noise while preserving knowledge.

Parameters* required
dry_runboolean
Preview clusters without compacting (default false)default: false
event_typestring
Event type to compact (default: lesson_learned)default: lesson_learned
min_cluster_sizeinteger
Minimum memories in a cluster to compact (default 3)default: 3
similarity_thresholdnumber
Minimum Jaccard similarity for clustering (0.0-1.0, default 0.6)default: 0.6
omega_checkpointSave a task checkpoint — captures current plan, progress, files touched, decisions, and key context. Use when: (1) context window is getting full, (2) completing a major milestone, (3) before starting a new session for an ongoing task. Checkpoints enable seamless session conti...9 params

Save a task checkpoint — captures current plan, progress, files touched, decisions, and key context. Use when: (1) context window is getting full, (2) completing a major milestone, (3) before starting a new session for an ongoing task. Checkpoints enable seamless session conti...

Parameters* required
planstring
Current plan or goals — what you're trying to accomplish
projectstring
Project path
progressstring
What's been completed, what's in progress, what remains
decisionsarray
Key technical decisions made during this task
next_stepsstring
What should be done next to continue this task
session_idstring
Current session ID
task_titlestring
Brief title of the current task (e.g., 'Frontend redesign Phase 2')
key_contextstring
Critical context needed to continue — patterns, variable names, API shapes, conventions
files_touchedobject
Map of file paths to change summaries (e.g., {'src/App.tsx': 'Added routing'})
omega_resume_taskResume a previously checkpointed task. Retrieves the latest checkpoint with full plan, progress, files, decisions, and next steps. Use at the start of a new session to continue where you left off.4 params

Resume a previously checkpointed task. Retrieves the latest checkpoint with full plan, progress, files, decisions, and next steps. Use at the start of a new session to continue where you left off.

Parameters* required
limitinteger
Number of checkpoints to retrieve (default 1 = latest only)
projectstring
Project path to filter checkpoints
verbositystring
How much context to return. 'full' = everything, 'summary' = plan + progress + next steps, 'minimal' = just next stepsone of full · summary · minimal
task_titlestring
Title of the task to resume (semantic search — doesn't need to be exact)
omega_remindSet a time-based reminder. OMEGA will surface it when the time arrives (at session start or during active sessions). Use for 'remind me in 1 hour to...' requests.5 params

Set a time-based reminder. OMEGA will surface it when the time arrives (at session start or during active sessions). Use for 'remind me in 1 hour to...' requests.

Parameters* required
textstring
What to be reminded about
contextstring
Optional context to include with the reminder (e.g. relevant file paths, decisions)
projectstring
durationstring
When to remind, e.g. '1h', '30m', '2d', '1w', '1d12h', '2 hours'
session_idstring
omega_remind_listList active reminders with their status and due times.1 params

List active reminders with their status and due times.

Parameters* required
statusstring
Filter by status (default: shows pending + fired)one of pending · fired · dismissed · all
omega_remind_dismissDismiss a reminder by its ID. Use after acknowledging a reminder.1 params

Dismiss a reminder by its ID. Use after acknowledging a reminder.

Parameters* required
reminder_idstring
The reminder memory ID to dismiss
omega_type_statsGet memory counts grouped by event type. Shows the composition of the memory store (how many decisions, lessons, errors, etc.).

Get memory counts grouped by event type. Shows the composition of the memory store (how many decisions, lessons, errors, etc.).

No parameter schema in public metadata yet.

omega_session_statsGet memory counts grouped by session. Shows which sessions have contributed the most memories (top 20).

Get memory counts grouped by session. Shows which sessions have contributed the most memories (top 20).

No parameter schema in public metadata yet.

omega_weekly_digestGet a weekly knowledge digest with stats, trends, and highlights. Shows new memories, session count, growth trends, type breakdown, and top topics.1 params

Get a weekly knowledge digest with stats, trends, and highlights. Shows new memories, session count, growth trends, type breakdown, and top topics.

Parameters* required
daysinteger
Number of days to include in the digest (default 7)default: 7
omega_protocolGet your coordination playbook — dynamically assembled operating instructions. Call at session start (step 2 after omega_welcome) or when you need protocol guidance. Returns context-sensitive rules based on project, peer activity, and learned lessons.2 params

Get your coordination playbook — dynamically assembled operating instructions. Call at session start (step 2 after omega_welcome) or when you need protocol guidance. Returns context-sensitive rules based on project, peer activity, and learned lessons.

Parameters* required
projectstring
Current project path for context-sensitive protocol rules.
sectionstring
Specific section or group: 'memory', 'coordination', 'coordination_gate', 'teamwork', 'context', 'reminders', 'diagnostics', 'entity', 'heuristics', 'git', 'what_next'. Groups: 'solo', 'multi_agent', 'full', 'minimal'. Omit for auto-detect based on peer activity.
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Categories
AI & LLM Tools
Registryactive
Packageomega-memory
TransportSTDIO
UpdatedMar 16, 2026
View 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.

Python 3.11+ PyPI License Tests


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.

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?"

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

FeatureOMEGAAnthropic MemoryMem0Zep
Works with any LLM/agentYesClaude onlyYesYes
Your data stays on your machineYesPartial*NoNo
No cloud dependencyYesNo (needs API)NoNo
Semantic search + knowledge graphYesNo (file CRUD)$249/moYes
Multi-agent coordinationYes (pro)Research previewNoNo
Works with Claude Code, Cursor, Claw CodeYesClaude onlyPartialNo
Free & open sourceYes (Apache 2.0)NoFreemiumFreemium

Anthropic's Memory Tool stores data client-side but requires Claude API calls for all memory operations. OMEGA runs entirely on-device, including embeddings (ONNX).

Anthropic Memory is for Anthropic. OMEGA is for everyone.

Architecture

     Claude Code  ·  Cursor  ·  Claw Code  ·  Any MCP Client
               │         │         │              │
               └─────────┴─────┬───┴──────────────┘
                               │ stdio/MCP
               ┌───────────────▼─────────────┐
               │   OMEGA MCP Server   │
               │   25 core tools      │
               └──┬──────────────────┘
                  │
         ┌────────▼──────────────┐
         │ Core Memory Engine    │
         │ (semantic search,     │
         │  embeddings, graphs)  │
         └─────┬─────────────────┘
               │
               ▼
         ┌──────────────────────────────────────┐
         │         omega.db (SQLite)             │
         │  memories | edges | embeddings        │
         └──────────────────────────────────────┘

Single database, modular handlers. Optional modules (coordination, router, entity, knowledge, profile) are available via omega-pro and register into the same server process. No separate daemons, no microservices.

MCP Tools Reference

OMEGA runs as an MCP server inside Claude Code. The core package provides 25 memory tools. omega-pro adds coordination, routing, entity, knowledge, and profile tools.

Memory (25 tools)

ToolWhat it does
omega_storeStore typed memory (decision, lesson, error, summary)
omega_querySemantic search with tag filters and contextual re-ranking
omega_welcomeSession briefing with recent memories and profile
omega_profileRead or update user profile
omega_delete_memoryDelete a specific memory by ID
omega_edit_memoryEdit the content of a memory
omega_list_preferencesList all stored user preferences
omega_healthDetailed health check with memory usage and recommendations
omega_backupExport or import memories for backup/restore
omega_lessonsCross-session lessons ranked by access count
omega_feedbackRecord feedback on a surfaced memory
omega_clear_sessionClear all memories for a specific session
omega_similarFind memories similar to a given one
omega_timelineMemories grouped by day
omega_consolidatePrune stale memories, cap summaries, clean edges
omega_traverseWalk the relationship graph
omega_compactCluster and summarize related memories
omega_checkpointSave task state for cross-session continuity
omega_resume_taskResume a previously checkpointed task
omega_remindSet a time-based reminder
omega_remind_listList active reminders
omega_remind_dismissDismiss a reminder
omega_type_statsMemory counts grouped by event type
omega_session_statsMemory counts grouped by session
omega_weekly_digestWeekly knowledge digest with stats and trends

Additional tools with omega-pro

ModuleToolsDescription
Coordination29File/branch locking, sessions, tasks, messaging, audit
Router10LLM routing, intent classification, model switching
Entity8Corporate entities, relationships, hierarchies
Knowledge5Document ingestion, semantic search, RAG
Profile3AES-256 encrypted personal data storage

CLI

CommandDescription
omega setupCreate dirs, download model, register MCP, install hooks (--hooks-only to skip MCP)
omega doctorVerify installation health
omega statusMemory count, store size, model status
omega query <text>Search memories by semantic similarity
omega store <text>Store a memory with a specified type
omega timelineShow memory timeline grouped by day
omega activityShow recent session activity overview
omega statsMemory type distribution and health summary
omega consolidateDeduplicate, prune, and optimize memory
omega compactCluster and summarize related memories
omega backupBack up omega.db (keeps last 5)
omega validateValidate database integrity
omega logsShow recent hook errors
omega migrate-dbMigrate legacy JSON to SQLite
Advanced Details

Hooks (7 processes, 11 handlers)

All hooks dispatch via fast_hook.py → daemon UDS socket, with fail-open semantics.

HookMatcherHandlersPurpose
SessionStartallsession_startWelcome briefing, session resume
Stopallsession_stopSummary
UserPromptSubmitallauto_captureAuto-capture lessons/decisions
PostToolUseEdit/Write/NotebookEditsurface_memoriesSurface relevant memories
PostToolUseBash/Readsurface_memoriesSurface relevant memories

With omega-pro, additional coordination handlers register automatically: session lifecycle, file/branch claim guards, heartbeat, and git push guards.

Storage

PathPurpose
~/.omega/omega.dbSQLite database (memories, embeddings, edges)
~/.omega/profile.jsonUser profile
~/.omega/hooks.logHook error log
~/.cache/omega/models/bge-small-en-v1.5-onnx/ONNX embedding model

Search Pipeline

  1. Vector similarity via sqlite-vec (cosine distance, 384-dim bge-small-en-v1.5)
  2. Full-text search via FTS5 (fast keyword matching)
  3. Type-weighted scoring (decisions/lessons weighted 2x)
  4. Contextual re-ranking (boosts by tag, project, and content match)
  5. Deduplication at query time

Memory Lifecycle

  • Dedup: SHA256 hash (exact) + embedding similarity 0.85+ (semantic) + Jaccard per-type
  • Evolution: Similar content (55-95%) appends new insights to existing memories
  • TTL: Session summaries expire after 1 day, lessons/preferences are permanent
  • Auto-relate: Creates related edges (similarity >= 0.45) to top-3 similar memories
  • Compaction: Clusters and summarizes related memories

Memory Footprint

  • Startup: ~31 MB RSS
  • After first query (ONNX model loaded): ~337 MB RSS
  • Database: ~10.5 MB for ~242 memories

What Gets Modified

omega setup modifies these files outside ~/.omega/:

  • ~/.claude.json — Adds omega-memory MCP server entry
  • ~/.claude/settings.json — Adds hook entries
  • ~/.claude/CLAUDE.md — Adds a managed <!-- OMEGA:BEGIN --> block

All changes are idempotent.

Troubleshooting

omega doctor shows FAIL on import:

  • Ensure pip install -e ".[server]" from the repo root
  • Check python3 -c "import omega" works

MCP server fails to start:

  • Run pip install omega-memory[server] (the [server] extra includes the MCP package)

MCP server not registered:

claude mcp add omega-memory -- python3 -m omega.server.mcp_server

Hooks not firing:

  • Check ~/.claude/settings.json has OMEGA hook entries
  • Check ~/.omega/hooks.log for errors

Development

pip install -e ".[server,dev]"
pytest tests/                # 2198+ tests
ruff check src/              # Lint

Uninstall

claude mcp remove omega-memory
rm -rf ~/.omega ~/.cache/omega
pip uninstall omega-memory

Manually remove OMEGA entries from ~/.claude/settings.json and the <!-- OMEGA:BEGIN --> block from ~/.claude/CLAUDE.md.

Contributing

  • Contributing Guide
  • Security Policy
  • Changelog
  • Report a Bug

License

Apache-2.0. See LICENSE.

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1
Agent Prompt Injection Firewall Mcp

csoai-org/agent-prompt-injection-firewall-mcp

The WAF for agents. Pattern-based + heuristic firewall scans prompts, RAG documents, tool argume...
Authenticated Multi Llm Agent

io.github.mikerawsonnz/authenticated-multi-llm-agent

Google-OAuth-gated LLM gateway: verify a Google ID token, then run a Gemini (Vertex AI) completion f