@caura-ai
基本情報
MemClaw — persistent memory for AI agent fleets (OSS)
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": {
"memclaw": {
"url": "http://localhost:8000/mcp",
"headers": {
"X-API-Key": "standalone"
}
}
}
}ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
上のボタンでサーバーのエンドポイントに接続し、ツール一覧を取得できます。
Memclaw is open-source fleet memory for multi-tenant, multi-agent AI fleets. Agents store what they learn, recall what the fleet knows, and compound knowledge across interactions instead of repeating mistakes. It is built for production deployments with dozens to thousands of agents sharing governed memory.
Clone the repository, configure a .env file (e.g., with an OpenAI API key), and run docker compose up -d to start Postgres + pgvector + Redis + the API. Write a memory via curl to /api/v1/memories and search with /api/v1/search. Alternatively, connect an MCP client using the server URL https://memclaw.net/mcp with an API key from the dashboard. Three deployment paths are offered: managed platform, self-hosted Docker, and OpenClaw plugin.
Memclaw is architected for fleets: scoped memory, cross‑agent outcome propagation, and fleet‑wide trust tiers, not a single long conversation. It competes on latency, token efficiency, and governance at scale.
PostgreSQL with pgvector for vector storage, Redis for the event bus, and optionally an AI provider (OpenAI, Gemini, Anthropic, OpenRouter) or a self‑hosted embedder (`BAAI/bge-m3`) for embeddings and enrichment.
In self‑hosted mode, data is stored in your local PostgreSQL instance. The managed platform (memclaw.net) hosts the database and infrastructure for you.
REST API and MCP transport. Auth uses tenant‑scoped or agent‑scoped API keys (prefix `mc_`). Standalone mode bypasses auth with `X-API-Key: standalone`.
Without an AI key, dummy embeddings are used (no semantic search). In production at eToro: 300+ agents, 26,500+ memories, 1,372 shared skills, 23 ms p50 search.
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