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Agentmemory MCP Server

@Obidel

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基本情報

カテゴリ

開発者ツール

トランスポート

stdio

作者

Obidel

投稿者

Obidel

Agentmemory MCP Server について

MCP-native memory layer for Claude Code, Cursor, Cline, Continue, and 16 other AI tools. Hybrid search (BM25 + pgvector + graph), self-hosted on Supabase + Vercel, 100% MIT, no paywall.

#memory#mcp#claude#cursor#ai-agents#self-hosted#pgvector#open-source

Agentmemory MCP Server の設定

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": {
    "agentmemory": {
      "command": "npx",
      "args": [
        "-y",
        "agentmemory"
      ],
      "env": {}
    },
    "agentmemory-cloud": {
      "url": "https://agentmemory-dusky.vercel.app/mcp"
    }
  }
}

Agentmemory MCP Server のツール

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。

概要

What is Agentmemory?

Agentmemory is a visual memory manager for AI agents, providing one source of truth for tools like Claude Code, Cursor, Cline, and Continue. It is an MCP-native, open-source (MIT) server that stores and retrieves agent memories with a graph view, semantic search, and project organization.

How to use Agentmemory?

Clone the repo and run npm install then npm run dev for the web UI (local mode), or npm run mcp to start the MCP server. Configure the MCP server in your AI tool’s settings (e.g., claude_desktop_config.json) with the command npx tsx /absolute/path/to/agentmemory/mcp/index.ts. Optionally sign in for cloud sync via Supabase.

Key features of Agentmemory

  • Visual memory graph with semantic relations
  • 9 MCP tools (add, search, list, find similar, delete, etc.)
  • 3 MCP resources (rules, graph, projects)
  • Supports 20+ AI tools (Claude, Cursor, Cline, etc.)
  • Self-hostable, no telemetry, no lock-in
  • Import/export to CLAUDE.md, .cursorrules, MemGPT JSON

Use cases of Agentmemory

  • Maintain persistent, searchable memory across AI agent sessions
  • Share context between different AI tools (e.g., Claude Desktop and Cursor)
  • Visualize and explore memory relationships with a force-directed graph
  • Organize memories by project for multi-project workflows
  • Sync memories across devices via optional cloud backend

よくある質問

1

What makes Agentmemory different from simple file-based memory?

It offers a visual graph, semantic search via vector embeddings, project separation, and MCP-native integration with many AI tools, all while being fully self-hostable and free.

2

What are the runtime requirements for Agentmemory?

Requires Node.js and npm. The MCP server runs via `tsx` with no build step. For the web UI, a modern browser suffices. Cloud sync requires a Supabase account (optional).

3

Where are memories stored by default?

In local-only mode, memories are stored in the browser’s `localStorage` for the web UI, or in `~/.agentmemory/` for the stdio MCP server. Cloud sync stores data in Supabase with row-level security.

4

Does Agentmemory have any limits or paid tiers?

No. It is 100% free forever with unlimited memories and projects, and no premium tiers or paywalls.

5

How do I authenticate for cloud sync?

Sign in to the hosted web UI, then retrieve a Supabase JWT from DevTools (`localStorage.getItem('sb-<project>-auth-token')`). The JWT expires after ~1 hour; refresh by re-running the command.

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