"Logseq - A Knowledge Management and Note-Taking App" matching MCP servers:

MCP server for a full-stack note-taking application, exposing CRUD tools for notes with SSE transport for AI agent integration.

An MCP server for interacting with Logseq graphs, enabling AI assistants to read, create, and manipulate Logseq content.

Enables AI agents to read Logseq notes, journals, tasks, pages and blocks—including embedded screenshots as viewable images—directly from the on-disk graph. It works read-only with Logseq closed and no network access, snapshotting the database so nothing can be modified.

Python stdio MCP server that interfaces with the Logseq local HTTP API, enabling tools to manage pages, blocks, queries, and graph configurations in Logseq.

Connects MCP-compatible AI assistants to Logseq graphs, enabling block-first operations, block references, and context graph building.

A Model Context Protocol server that enables AI agents to interact with a local Logseq instance, allowing operations like creating pages, managing blocks, and searching across a knowledge graph.

A Model Context Protocol server that enables AI agents to interact with local Logseq knowledge graphs, supporting operations like creating/editing pages and blocks, searching content, and managing journal entries.

Enables interaction with your Logseq personal knowledge management system via MCP, allowing retrieval of tagged notes and todo lists through Logseq's HTTP API.

Interacts with LogSeq via its API.

Provides an agent-first note-taking system designed from the ground up for AI collaboration. Organizes your notes as a local vault of ordinary markdown files with semantic note types.

Enables AI assistants like Claude to directly read, write, search, and navigate your local Logseq knowledge graph, including managing journals, pages, backlinks, and page relationships without manual copy-pasting.

A NestJS-based server that enables AI agents to interact with Logseq graphs through its HTTP API for managing notes, journals, and blocks. It features specialized tools for project development tracking, including progress logs, technical decisions, and workflow prompts.

Connects AI assistants to Logseq knowledge graphs to read, write, and search pages, blocks, and journals via the Model Context Protocol. It features 17 tools for full graph management, including CRUD operations, batch block insertion, and full-text search.

Enables structured note-taking with markdown support, dynamic tagging system, advanced search capabilities, and markdown export functionality through natural language conversations in Claude Desktop.

AI assistant integration with Logseq knowledge graph: 21 tools to read, write, query, and search notes, enabling seamless interaction with your notes.

Enables AI assistants to interact with your local Logseq knowledge base through advanced search, content creation, template management, and knowledge organization with privacy-first, local-only operations.

A proof-of-concept MCP server for AI assistant note-taking, enabling adding notes, fetching the latest note, and summarizing all notes.

A Model Context Protocol server that provides AI assistants with structured access to your Logseq knowledge graph, enabling retrieval, searching, analysis, and creation of content within your personal knowledge base.

A local, read-only MCP server (plus CLI) over your own stock/ETF transaction log. A deterministic core computes drawdown-first risk with bootstrap confidence intervals and validates targets with walk-forward verdicts. The assistant narrates, but the number fence makes it structurally impossible for the model to produce a figure.

A Model Context Protocol (MCP) server for developer note-taking, allowing users to create, manage, and export development notes with tags, status, and priority.