Ergut MCP Logseq Server

The Ergut MCP Logseq Server bridges the gap between AI assistants and the powerful knowledge‑management platform LogSeq. By exposing LogSeq’s REST API through a standard Model Context Protocol interface, the server enables Claude and other MCP‑compliant assistants to query, modify, and organize notes as if they were native tools. This eliminates the need for manual API calls or custom integrations, allowing developers to focus on higher‑level workflows while maintaining full control over their personal knowledge graph.

Solving the Knowledge‑Graph Integration Problem

LogSeq is a popular graph‑based note system, yet its API requires authentication, URL management, and data formatting that can be cumbersome to handle in conversational agents. The MCP server abstracts these details behind a set of intuitive tools: listing graphs, retrieving page content, searching across the graph, and performing CRUD operations on pages. Developers can embed these capabilities directly into prompts, letting the assistant autonomously navigate and manipulate their LogSeq data without exposing tokens or writing boilerplate code.

Core Capabilities

• Graph Management – returns all available LogSeq graphs, enabling assistants to select the context in which subsequent actions occur.
• Page Discovery – enumerates every page in the active graph, providing a quick overview of available content.
• Content Access – fetches the raw Markdown of a specific page, allowing the assistant to read or analyze notes.
• Search – performs keyword queries across the entire graph, returning matching pages and snippets.
• Page Lifecycle – , , and let the assistant create new entries, edit existing ones, or remove obsolete pages—all while preserving LogSeq’s internal metadata and relationships.

These tools are designed to be called automatically by the AI once a user issues a high‑level instruction, ensuring seamless interaction without manual intervention.

Practical Use Cases

• Meeting Management – Summarize the latest meeting notes, create a new page for tomorrow’s agenda, or update an ongoing project status page.
• Research Synthesis – Search for all pages that mention a specific topic, then generate an overview of the collected insights.
• Knowledge Curation – Automate the cleanup of outdated pages or the migration of notes between graphs.
• Workflow Automation – Integrate LogSeq queries into broader productivity pipelines, such as pulling data into a task manager or generating daily digests.

These scenarios illustrate how the server turns routine LogSeq interactions into conversational actions, saving time and reducing friction.

Seamless Integration with AI Workflows

The server is configured via environment variables or a JSON block in the MCP configuration, keeping sensitive tokens out of source code. Once running, any MCP‑compatible client can invoke the LogSeq tools through simple tool calls. The assistant’s prompt can explicitly instruct it to “use LogSeq” before performing an operation, ensuring that the tool is called automatically. This pattern keeps prompts clean and lets developers focus on higher‑level logic rather than low‑level API handling.

Unique Advantages

• Zero‑Code Interaction – Developers can leverage LogSeq without writing any API wrappers, thanks to the MCP abstraction.
• Secure Token Management – Credentials are handled through environment variables or the server config, avoiding hard‑coded secrets.
• Extensible Tool Set – The modular design allows future expansion (e.g., adding tagging or graph‑visualization tools) without disrupting existing workflows.
• Built for Debugging – The recommended MCP Inspector integration provides real‑time insights into tool calls, making troubleshooting straightforward even for complex interactions.

In summary, the Ergut MCP Logseq Server transforms a powerful knowledge‑management platform into an AI‑friendly resource, empowering developers to build intelligent assistants that can read, write, and organize their notes with natural language commands.