This MCP server, developed by Salih, provides a seamless interface for AI assistants to interact with LogSeq via its API. Built using Python and the MCP library, it offers a range of tools for managing LogSeq graphs, including listing pages, searching content, and creating or updating pages. The server abstracts the complexities of API communication, allowing AI systems to easily integrate with LogSeq for note-taking and knowledge management tasks. It's particularly useful for scenarios requiring automated interaction with LogSeq, such as summarizing meeting notes, updating project statuses, or performing content searches across multiple pages. By bridging AI capabilities with LogSeq's functionality, this implementation enables more efficient and intelligent personal knowledge management workflows.
暂无评论. 成为第一个评论的人！
登录以参与讨论
Browse your graph; parameters include 'sort' for ordering (e.g., 'updated') and 'updated_since' to find recently modified pages.
Read page content from the graph.
Add new pages with structured blocks. Example use: 'Create a meeting notes page with agenda items'.
Modify pages in either append or replace modes.
Remove pages from the graph.
Remove a specific block by its UUID.
Edit content of a block using its UUID.
Retrieve a block by its UUID along with its properties and children.
Find content across the graph using a search query.
Execute Logseq DSL queries (note: raw datalog not supported).
Search for pages by specific properties.
List all pages within a specified namespace.
Provide a hierarchical view of pages in a namespace.
Rename a page while updating all references.
Find all pages that link to a specified page.
Insert child or sibling blocks under a specified block.
Set class properties on a block in DB-mode.
Perform a semantic search across notes by meaning.
Sync the vector database with the graph files.
Show the health and staleness status of the vector database.
