Logseq (Knowledge Management) MCP Server
Manage your knowledge base via Logseq — create pages, insert outliner blocks, and search across your local graph.
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What is the Logseq MCP Server?
The Logseq MCP Server gives AI agents like Claude, ChatGPT, and Cursor direct access to Logseq via 10 tools. Manage your knowledge base via Logseq — create pages, insert outliner blocks, and search across your local graph. Powered by the Vinkius - no API keys, no infrastructure, connect in under 2 minutes.
Built-in capabilities (10)
Tools for your AI Agents to operate Logseq
Ask your AI agent "Search my Logseq graph for 'smart building research'" and get the answer without opening a single dashboard. With 10 tools connected to real Logseq data, your agents reason over live information, cross-reference it with other MCP servers, and deliver insights you would spend hours assembling manually.
Works with Claude, ChatGPT, Cursor, and any MCP-compatible client. Powered by the Vinkius - your credentials never touch the AI model, every request is auditable. Connect in under two minutes.
Why teams choose Vinkius
One subscription gives you access to thousands of MCP servers - and you can deploy your own to the Vinkius Edge. Your AI agents only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure and security, zero maintenance.
Build your own MCP Server with our secure development framework →Vinkius works with every AI agent you already use
…and any MCP-compatible client
Logseq (Knowledge Management) MCP Server capabilities
10 toolsEditor.createPage` deploying new pages including native markdown contents inside the local map. Create explicitly a new organized page in the Logseq target Graph
Editor.removeBlock` erasing specific limit bounds dropping child dependencies explicitly. Delete an explicit active Block target removing explicit nodes safely
Editor.deletePage` removing content arrays destroying metadata loops. Delete an entire explicit active Logseq page irreversibly
Validate environment limits identifying explicit current graph arrays parsed natively
Retrieve metadata for a specific Logseq page by mapping name or UUID limits
Extract the hierarchical explicit native tree limit array block from a page map
Editor.insertBlock` natively adding outliner chunks executing explicit properties updating nodes immediately. Append an explicitly managed Block limit tracking inside the specific Logseq map
List all pages in the current Logseq graph
Execute local queries extracting explicitly bound text targets crossing Graph indices
Editor.updateBlock` safely preserving UUID bounds retaining linking indices natively. Modify raw properties explicitly bound inside a given Logseq tracked block
What the Logseq (Knowledge Management) MCP Server unlocks
Connect your Logseq instance to any AI agent and take full control of your privacy-first knowledge graph and personal documentation through natural conversation.
What you can do
- Graph Orchestration — List all pages and retrieve detailed hierarchical block trees representing your local outliner data directly from your agent
- Page Management — Create new organized pages or journal entries and manage their lifecycle including irreversible deletion of metadata loops securely
- Block Operations — Append, update, or delete individual outliner blocks, preserving precise UUID bounds and linking indices within your graph
- Deep Content Search — Execute local queries to extract explicitly bound text targets across your entire knowledge base, including titles and namespaces
- Hierarchical Inspection — Extract deeply nested outliner hierarchies to understand the complex structural relationships between your ideas and projects
- Environment Audit — Identify current active graph paths and local database directories to verify your agent is targeting the correct knowledge store
How it works
1. Subscribe to this server
2. Enable the HTTP API in your Logseq Settings
3. Enter your Logseq API Token and Host URL (e.g., http://localhost:12315)
4. Start managing your local graph from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Knowledge Workers — organize research and meeting notes through natural conversation without manually navigating the Logseq outliner
- Software Developers — manage technical documentation and project logs directly from your IDE or workspace terminal
- PKM Enthusiasts — audit complex graph structures and perform bulk block updates to maintain a clean and optimized personal knowledge base
Frequently asked questions about the Logseq (Knowledge Management) MCP Server
Can I search across all my Logseq pages using my agent?
Yes. Use the search_content tool to execute deep property searches across your graph indices. Your agent will filter titles, namespaces, and block scopes to find the exact information you need.
How do I add a new note to a specific page?
Use the insert_block tool and provide the target Page name or ID. Your agent will drive the Logseq editor to add a new outliner chunk with your markdown content immediately.
Can my agent retrieve the hierarchical structure of a long page?
Absolutely. The get_page_blocks tool extracts the full hierarchical tree from a page map. Your agent will return the nested arrays of outliner blocks, ensuring you have the complete structural context of your data.
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Connect Logseq (Knowledge Management) with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
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GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
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Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Give your AI agents the power of Logseq MCP Server
Production-grade Logseq (Knowledge Management) MCP Server. Verified, monitored, and maintained by Vinkius. Ready for your AI agents — connect and start using immediately.