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qualityInteracts with LogSeq via its API.
Last updated -
2
25
Python
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Why this server?
This server allows interaction with LogSeq through its API, enabling AI to create and manage pages and blocks in your LogSeq knowledge graph.
Why this server?
This project provides an MCP server to connect AI models with Obsidian vaults, which can act as local knowledge bases, enabling the AI to access and manipulate notes and folder structures. Since Logseq and Obsidian are similar, this could be useful.
Why this server?
This server connects Claude Desktop (or any MCP client) to your Markdown notes in an Obsidian vault. Since Logseq and Obsidian are similar, this could be useful.
Why this server?
A basic implementation of persistent memory using a local knowledge graph, similar to how Logseq is structured. This lets Claude remember information about the user across chats.
Why this server?
This project is based on the Knowledge Graph Memory Server from the MCP servers repository and retains its core functionality, which could be beneficial for managing knowledge like Logseq.
Why this server?
Allows Claude and other LLMs to manage persistent memories across conversations through text file storage, which can be relevant for managing Logseq data.
Why this server?
A basic implementation of persistent memory using a local knowledge graph. This lets Claude remember information about the user across chats; could be useful for Logseq users who want a way to have Claude remember their notes.
Why this server?
Improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path. This lets Claude remember information about the user across chats, which could be useful for Logseq.
Why this server?
Obsidian vault connector for Claude Desktop - enables reading and writing Markdown notes using Model Context Protocol (MCP). Could be useful if you use both Logseq and Obsidian.