What tools does MCP server for LogSeq provide?
It provides seven tools: `list_graphs`, `list_pages`, `get_page_content`, `search`, `create_page`, `update_page`, and `delete_page`.
@ergut
Basic information
MCP server to interact with LogSeq via its Local HTTP API - enabling AI assistants like Claude to seamlessly read, write, and manage your LogSeq graph.
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"mcp-logseq-server": {
"command": "uv",
"args": [
"sync"
]
}
}
}Lists all available graphs
Lists all pages in the current graph
Return the content of a single page
Search for content across all pages
Create a new page
Update content of an existing page
Delete a page
MCP server for LogSeq is an MCP server that enables interaction with LogSeq through its API. It provides a set of tools for reading and writing data, designed for LogSeq users who want to manage their knowledge graph with an AI assistant such as Claude.
Configure the server by providing a LOGSEQ_API_TOKEN and the LOGSEQ_API_URL (default http://localhost:12315) either in the MCP server config or via a .env file. Then run uvx mcp-logseq. After adding it to the MCP client, instruct the assistant to use LogSeq; it will call the available tools automatically.
list_graphs)list_pages)get_page_content)search)create_page)update_page)delete_page)It provides seven tools: `list_graphs`, `list_pages`, `get_page_content`, `search`, `create_page`, `update_page`, and `delete_page`.
You can add the environment variables `LOGSEQ_API_TOKEN` and `LOGSEQ_API_URL` directly in the MCP server configuration (JSON) or create a `.env` file in the working directory.
The default API URL is `http://localhost:12315`. You must provide your own `LOGSEQ_API_TOKEN`.
Use the MCP Inspector by running `npx @modelcontextprotocol/inspector uv --directory <path> run mcp-logseq`.
It is built with Python and uses `uv` as the package manager. The recommended way to run it is via `uvx mcp-logseq`.

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