Where is the source code for Omega Memory?
The source code is linked from the repository URL on this page.
@omega-memory
基本情報
Persistent memory for AI coding agents
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"omega-memory": {
"command": "uv",
"args": [
"tool",
"install",
"omega-memory[server]"
]
}
}
}Store a memory (decision, lesson, error, preference, ...)
Search memories: semantic, exact phrase, timeline, or browse
Session briefing: recent context, reminders, profile
Operating rules for the session
Save task state for cross-session continuity
Resume a checkpointed task
Edit, delete, supersede, rate, or link one memory; find similar ones
Read or update the user profile and preferences
Set, list, or dismiss time-based reminders
Health, consolidation, compaction, backup and restore
Type breakdown, session stats, weekly digest
Find contradictions; trace how a topic's decisions evolved
Review a diff with memory of your codebase's conventions
Compact, task-aware memory packet for the current work
Persistent memory for AI coding agents
The README includes setup instructions such as python3.12 -m venv ~/.venvs/omega # any Python 3.11 or newer.
The source code is linked from the repository URL on this page.
If the README contains a parseable MCP configuration block, it is shown in the Config tab.

Ask your Takibi Base collections anything; get answers with cited passages and a support score.

Mess in, magic out: pour in your D&D and TTRPG notes and LoreKeeper keeps them as a private store for your world. Ask Claude or ChatGPT about it, or build a sourcebook.

Model Context Protocol Servers

Serve your docs to AI agents over SSH and MCP. Agents use ls, cat, grep, find, and pipes against a virtual filesystem backed by your documentation. Identity-scoped access, governed writing with human approval, and portab
Shared, serverless, conflict-free memory for AI agents: a multi-machine drop-in for the MCP memory knowledge graph.
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