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    An MCP server that stores notes as Markdown files on your machine, enabling you to save, search, and manage notes through natural language with Claude Code or Claude Desktop.
    5
    MIT
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    On Board is a local MCP server that gives multiple AI agents and IDEs a shared project memory, ticket queue, and handoff history, so agents can seamlessly continue each other's work. It supports agent-to-agent wake events, enabling autonomous workflows like reject-fix-resubmit cycles without human relay.
    30
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    Apache 2.0
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    A personal notes MCP server that allows AI assistants to create, search, edit, and manage notes stored in a local SQLite database.
    6
    MIT
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    A lightweight Notion MCP server that minimizes token usage by returning Markdown instead of raw JSON, enabling efficient read/write operations on Notion pages.
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    MIT
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    MCP server for a personal notes/knowledge base that enables AI assistants to create, search, and retrieve notes using natural language. It exposes tools like create_note and search_notes, resources for each note, and a summarize_tag prompt.
    6
    MIT
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    Enables interaction with Notion workspaces through a comprehensive set of tools for managing pages, blocks, databases, users, comments, and search. Provides both a clean Python API and an MCP server for use with Claude Desktop.
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    A personal knowledge management system built on the Model Context Protocol that transforms daily notes into organized, searchable knowledge.
    9
    6 npm
    MIT
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    End-to-end-encrypted markdown notes that double as agent memory: on-device semantic search (no API key), scoped and revocable agent keys, a hosted connector for Claude.ai and ChatGPT, and a self-hostable relay that stores ciphertext only.
    9
    701 npm
    MIT
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    A note-taking knowledge base MCP server that enables CRUD operations on notes with tags, resource listing/detail, and prompt-based analysis and brainstorming.
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    A Notion MCP server that enables searching, exporting, and importing pages as markdown using browser credentials without admin or OAuth setup.
    24 npm
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    MIT
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    A token-optimized MCP server for Notion that reduces context window usage by 73% while preserving full functionality, enabling AI assistants to interact with Notion efficiently.
    15 npm
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    MIT
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    A note-taking MCP server that lets you add, delete, and view dated notes, with an HTML view and REST API. Supports SQLite or Postgres and can run as a local stdio server or hosted HTTP service.
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    MCP server enabling AI agents to read and append to a user's daily bullet notebook, with entity-graph tagging and append-only, auditable notes.
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    Provides an AI agent with a searchable markdown notes vault, offering tools to create, read, list, search, update, and delete notes stored as plain .md files.
    6
    MIT
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    Privacy-first local document search using semantic search. Runs entirely on your machine with no cloud services, supporting PDF, DOCX, TXT, and Markdown files.
    9
    4,565 npm
    426
    MIT
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    Enables AI assistants to persistently save, list, search, and delete typed notes through MCP tools, with tag filtering and keyword ranking. Notes are stored in a JSON file using atomic writes and validated inputs.
    7
    325 npm
    3
    MIT
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    Unofficial Notion MCP server built on Notion's private API (token_v2 cookie). Gives LLM agents full read/write access to the entire workspace — no integration token and no per-page sharing.
    11
    13 npm
    4
    MIT
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    Personal knowledge management server with note CRUD, semantic search, git versioning, wiki linking, tags, glossary, and fact graph capabilities.
    38
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    Apache 2.0
  • F
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    Enables indexing and retrieving notes with full-text search using SQLite, plus building knowledge graphs to find relationships between concepts. Supports natural language note management, tagging, and semantic connections.
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    Fast, read-only MCP server for Notion that reads directly from local SQLite cache, enabling instant access to Notion pages, databases, and users without API calls or rate limits.
    2
    MIT