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mcp-pkm-logseq MCP server

@ruliana

リポジトリ

基本情報

カテゴリ

メモリとナレッジ

ライセンス

MIT

トランスポート

stdio

作者

ruliana

mcp-pkm-logseq MCP server について

A fairly customizable MCP server for Logseq

mcp-pkm-logseq 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": {
    "mcp-pkm-logseq": {
      "command": "uv",
      "args": [
        "sync"
      ]
    }
  }
}

mcp-pkm-logseq 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。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is mcp-pkm-logseq?

mcp-pkm-logseq is an MCP server that enables AI assistants to interact with your Logseq Personal Knowledge Management system. It provides tools to retrieve notes and todos from your Logseq graph, guided by a custom instructions page you create. It is intended for users who want LLM-powered access to their Logseq knowledge base.

How to use mcp-pkm-logseq?

Install via uvx mcp-pkm-logseq and configure the environment variables LOGSEQ_API_KEY (default "this-is-my-logseq-mcp-token") and LOGSEQ_URL (default "http://localhost:12315"). Enable Logseq’s built-in HTTP API server in Settings → Advanced → Developer mode, set your API token, then configure your MCP client (e.g., Claude Desktop, Claude Code, Cursor) with the server command and environment variables. A page named “MCP PKM Logseq” should be created in your graph to serve as an AI guide.

Key features of mcp-pkm-logseq?

  • Provides a guide resource (logseq://guide) for assistant instructions.
  • Retrieve personal notes by topic and date range.
  • Retrieve todo items filtered by done status and date range.
  • Configurable API token and Logseq server URL.
  • Integrates with Logseq’s HTTP API (port 12315 default).

Use cases of mcp-pkm-logseq?

  • An AI assistant retrieves notes tagged with specific topics from your Logseq graph.
  • A chatbot fetches your current or past todos to help with task management.
  • A personal knowledge assistant uses the guide page to learn your tagging conventions before searching.

よくある質問

1

What environment variables does mcp-pkm-logseq require?

`LOGSEQ_API_KEY` (default: `"this-is-my-logseq-mcp-token"`) for authentication and `LOGSEQ_URL` (default: `"http://localhost:12315"`) for the Logseq HTTP API endpoint.

2

How do I enable the Logseq HTTP API?

Open Logseq, go to Settings → Advanced, enable “Developer mode” and “HTTP API Server”, then set your API token to match the `LOGSEQ_API_KEY` value.

3

Where do I configure mcp-pkm-logseq for Claude Desktop?

On macOS: `~/Library/Application Support/Claude/claude_desktop_config.json`; on Windows: `%APPDATA%/Claude/claude_desktop_config.json`. Add the server under `mcpServers` with `"command": "uvx"` and `"args": ["mcp-pkm-logseq"]`.

4

What is the “MCP PKM Logseq” page for?

It is a guide page you create in your Logseq graph containing your tagging system, workflows, naming conventions, and search preferences. The server exposes it as a resource so the AI assistant can understand how to interact with your knowledge base.

5

How can I debug the server during development?

Use the MCP Inspector by running `npx @modelcontextprotocol/inspector uv --directory <path> run mcp-pkm-logseq`. This provides a browser-based debugging interface.

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