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    A local MCP server for low-token co-reading: import a book, split it into chapter-sized chunks, read it chunk by chunk, and keep notes so a session can resume without re-reading the whole book.
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    A Model Context Protocol server that wraps the official Obsidian CLI to allow AI agents to read, write, search, and manage notes within an Obsidian vault. It provides 16 specialized tools for comprehensive vault interaction, including note management, task tracking, and metadata manipulation.
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    MIT
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    This project implements a Model Context Protocol (MCP) server for connecting AI models with Obsidian knowledge bases. Through this server, AI models can directly access and manipulate Obsidian notes, including reading, creating, updating, and deleting notes, as well as managing folder structures.
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    Enables AI models to interact with the Get笔记 (GetNotes) platform via its Open API. It supports managing notes, organizing knowledge bases, and handling tags through natural language commands.
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    A Python package that enables LLM models to interact with Memos server through the Model Context Protocol interface, allowing search, creation, retrieval, and management of memos.
    Last updated
    4
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    MIT
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    An enhanced MCP server for the Yuque knowledge base that provides advanced document management, directory tree navigation, and structural adjustment capabilities. It enables AI assistants to manage complex content hierarchies, move nodes, and execute general OpenAPI requests within the Yuque platform.
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    Provides a hybrid search engine for Obsidian vaults, enabling LLM agents to query notes with BM25 keyword and vector semantic search, metadata filtering, and sibling-document retrieval.
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    MIT
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    An Obsidian plugin that runs an MCP server, enabling external LLM tools to read, search, create, and modify notes in your vault via HTTP or stdio transport.
    Last updated
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    MIT