Logseq MCP Tools

Logseq MCP Tools

The Logseq MCP Tools server bridges the gap between an AI assistant and a user’s personal knowledge graph in Logseq. By exposing a set of well‑defined tools through the Model Context Protocol, it allows Claude or any MCP‑compliant client to query, manipulate, and summarize data that lives inside Logseq without leaving the chat interface. This eliminates the need to manually open Logseq, copy‑paste notes, or run separate scripts whenever you want to reference your own information.

What the server does is twofold: first, it translates Logseq’s HTTP API into MCP tool calls; second, it enriches those calls with natural‑language processing to make the data more useful. For example, a user can ask Claude to “show me my recent journal entries” and the assistant will automatically call , parse the date range, pull all relevant pages, and return a concise, readable summary. The same mechanism can create new pages () or search for existing ones (), letting the assistant act as a smart notebook rather than just a conversational partner.

Key features include:

• Page discovery () that lists every node in the graph, useful for exploratory tasks or building indexes.
• Targeted content retrieval () that fetches the full Markdown of any page by name.
• Temporal summarization () that aggregates journal entries over arbitrary date ranges, highlights recurring concepts, and presents the data in a clean format.
• Dynamic page creation () enabling the assistant to add new thoughts or tasks directly into Logseq.
• Search capability () that performs fuzzy matching on page titles, supporting quick navigation.

Real‑world scenarios range from daily knowledge management—where an assistant can pull up yesterday’s notes or remind you of pending tasks—to research workflows, where it can surface all pages linked to a specific concept and generate an overview. In software development teams, the server can help maintain technical documentation by creating or updating pages on demand. For personal productivity, it turns Claude into a living diary that automatically keeps your Logseq entries organized and accessible.

Integration is straightforward: the MCP server runs locally, exposing a JSON‑based API that any Claude deployment can consume. Developers can add it as a service in Claude Desktop, Cursor, or via the Anthropic API, and then refer to Logseq data directly in prompts. The server’s design emphasizes minimal friction—no extra authentication steps beyond the Logseq token—and leverages Logseq’s own HTTP API, ensuring that data remains secure and consistent.

Overall, the Logseq MCP Tools server gives AI assistants a powerful, structured interface to your personal knowledge graph, turning conversations into actionable insights and automated note‑taking.