Mcp Logseq Server

Overview

The MCP LogSeq Server bridges the gap between Claude’s conversational intelligence and the powerful graph‑based knowledge base of LogSeq. By exposing a suite of tools that read, create, and manipulate pages through the LogSeq HTTP API, this server eliminates the friction of manual data transfer. Developers can keep their information in a single, richly linked repository while letting an AI assistant surface insights, generate summaries, and automate routine updates—all without leaving the LogSeq environment.

For developers building AI‑enhanced workflows, the server provides a turnkey solution to integrate LogSeq into any MCP‑compatible client. Once the LogSeq API is enabled and an authentication token is generated, a single command registers the server with Claude. From there, any prompt that references page names, content queries, or update instructions can be translated into precise API calls. This seamless integration preserves the native LogSeq experience—links, tags, and embedded media remain intact—and gives Claude a direct, real‑time view of the graph.

Key capabilities include:

• Page discovery and navigation () to enumerate the entire graph.
• Content retrieval () for deep dives into specific topics.
• Dynamic page lifecycle management via , , and .
• Cross‑page search () that spans the whole graph, enabling theme extraction and trend spotting.

These primitives empower use cases such as automated status reports (“Analyze all my project notes from the past month”), knowledge‑base expansion (“Create a weekly review page from recent notes”), and research synthesis (“Compare my notes on React vs Vue”). The server’s design aligns with the principles of zero context switching and intelligent organization, allowing developers to keep their workflows uninterrupted while leveraging Claude’s natural language understanding.

In practice, a developer can ask Claude to “Create a new page called ‘Today’s Standup’ with my meeting notes” and the server will translate that into a call, embedding the content directly in LogSeq. For more complex tasks—such as generating a knowledge map or summarizing customer feedback across multiple pages—the server provides the raw data, letting Claude apply advanced NLP techniques before writing back to LogSeq. This tight coupling of AI reasoning and persistent storage makes the MCP LogSeq Server a standout tool for teams that rely on structured knowledge bases to drive decision‑making, documentation, and continuous learning.