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A tool for organizing, merging, and rephrasing Google Keep notes

  • Why this server?

    Allows listing, reading, and searching files in Google Drive, which could include Google Keep notes if they are stored there.

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    Enables integration with Google Drive for listing, reading, and searching over files, supporting various file types with automatic export for Google Workspace files.
    1,327
    9
    JavaScript
    MIT License
  • Why this server?

    Integrates with Google Drive to enable listing, searching, and reading files, plus reading and writing to Google Sheets which could be useful for sorting and organizing data.

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    Integrates with Google Drive to enable listing, searching, and reading files, plus reading and writing to Google Sheets.
    203
    39
    TypeScript
    MIT License
  • Why this server?

    Could be used to store and organize the extracted information from the notes.

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    A basic implementation of persistent memory using a local knowledge graph. This lets Claude remember information about the user across chats.
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    9,068
    37,968
    JavaScript
    MIT License
  • Why this server?

    Allows storing, managing, and summarizing notes, which are useful to extract relevant information.

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    This server enables users to store, manage, and summarize notes using a custom URI scheme, with functionality to add new notes and generate summaries with varying levels of detail.
    3
    Python
    • Apple
  • Why this server?

    While focused on Apple Notes, it hints at RAG (Retrieval Augmented Generation) capabilities suitable for semantic search and summarization, useful for merging notes by meaning.

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    Enables semantic search and RAG (Retrieval Augmented Generation) over your Apple Notes.
    158
    TypeScript
    • Apple
  • Why this server?

    Provides semantic memory and persistent storage, useful for remembering the meaning of notes and retrieving them later.

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    Provides semantic memory and persistent storage for Claude, leveraging ChromaDB and sentence transformers for enhanced search and retrieval capabilities.
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    167
    Python
    MIT License
    • Linux
  • Why this server?

    Offers RAG (Retrieval-Augmented Generation) capabilities, enabling semantic document search for more efficient information retrieval from notes.

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    Provides RAG capabilities for semantic document search using Qdrant vector database and Ollama/OpenAI embeddings, allowing users to add, search, list, and delete documentation with metadata support.
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    4
    TypeScript
    Apache 2.0
  • Why this server?

    Provides unified access to multiple search engines and AI tools for content processing and enhancement, beneficial for finding relevant notes and rephrasing them.

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    🔍 A Model Context Protocol (MCP) server providing unified access to multiple search engines (Tavily, Brave, Kagi), AI tools (Perplexity, FastGPT), and content processing services (Jina AI, Kagi). Combines search, AI responses, content processing, and enhancement features through a single interface.
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    30
    TypeScript
    MIT License
    • Linux
  • Why this server?

    Allows access and manipulation of Obsidian notes, which could be a store for personal notes.

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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.
    598
    7
    JavaScript