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mcp-logseq-server

MCP.Pizza Chef: ergut

The mcp-logseq-server is an MCP server designed to integrate AI assistants like Claude with LogSeq through its Local HTTP API. It provides structured tools to list graphs and pages, retrieve and search page content, and create, update, or delete pages within a LogSeq graph. This server enables seamless, real-time interaction with your LogSeq knowledge base, empowering AI models to assist with note-taking, content management, and knowledge retrieval in a secure and efficient manner.

Use This MCP server To

List all available LogSeq graphs Retrieve content of specific LogSeq pages Search across all pages in a LogSeq graph Create new pages in LogSeq Update existing LogSeq pages Delete pages from LogSeq Summarize meeting notes stored in LogSeq Manage project documentation within LogSeq

README

MCP server for LogSeq

MCP server to interact with LogSeq via its API.

Components

Tools

The server implements multiple tools to interact with LogSeq:

  • list_graphs: Lists all available graphs
  • list_pages: Lists all pages in the current graph
  • get_page_content: Return the content of a single page
  • search: Search for content across all pages
  • create_page: Create a new page
  • update_page: Update content of an existing page
  • delete_page: Delete a page

Example prompts

It's good to first instruct Claude to use LogSeq. Then it will always call the tool.

Example prompts:

  • Get the contents of my latest meeting notes and summarize them
  • Search for all pages where Project X is mentioned and explain the context
  • Create a new page with today's meeting notes
  • Update the project status page with the latest updates

Configuration

LogSeq API Configuration

You can configure the environment with LogSeq API settings in two ways:

  1. Add to server config (preferred)
{
  "mcp-logseq": {
    "command": "uvx",
    "args": [
      "mcp-logseq"
    ],
    "env": {
      "LOGSEQ_API_TOKEN": "<your_api_token_here>",
      "LOGSEQ_API_URL": "http://localhost:12315"
    }
  }
}
  1. Create a .env file in the working directory with the required variables:
LOGSEQ_API_TOKEN=your_token_here
LOGSEQ_API_URL=http://localhost:12315

Development

Building

To prepare the package for distribution:

  1. Sync dependencies and update lockfile:
uv sync

Debugging

Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we recommend using the MCP Inspector.

You can launch the MCP Inspector via npm with:

npx @modelcontextprotocol/inspector uv --directory /path/to/mcp-logseq run mcp-logseq

mcp-logseq-server FAQ

How do I configure the mcp-logseq-server to connect with my LogSeq instance?
You can configure the server by adding LogSeq API settings directly to the server configuration file or by setting environment variables for the Local HTTP API endpoint.
Can the mcp-logseq-server handle multiple LogSeq graphs?
Yes, it supports listing and interacting with multiple graphs, allowing AI assistants to manage different knowledge bases.
What operations can AI assistants perform through this server?
AI assistants can list graphs and pages, get page content, search pages, create, update, and delete pages within LogSeq.
Is the mcp-logseq-server compatible with AI models other than Claude?
Yes, it is designed to work with various AI assistants and LLM providers such as OpenAI, Claude, and Gemini.
How does the server ensure secure interaction with LogSeq data?
The server uses scoped API access via the Local HTTP API, ensuring that AI assistants only perform authorized operations within the configured environment.
Can I use the mcp-logseq-server to automate note-taking workflows?
Absolutely, it enables AI to read, write, and update notes automatically, streamlining knowledge management.
Does the server support real-time updates to LogSeq pages?
Yes, AI assistants can update pages in real-time, reflecting the latest information and edits.
What is the recommended way to start using the mcp-logseq-server with an AI assistant?
Begin by instructing the AI to use LogSeq tools, then it will automatically call the appropriate API endpoints for tasks.