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260,856 tools. Last updated 2026-07-05 08:54

"Notes or documentation related to 'rag'" matching MCP tools:

Matching MCP Servers

  • A
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    Enables semantic search and retrieval over an Obsidian vault using local or API-based embeddings, allowing AI assistants to find notes by meaning, get related content, and pull context during conversations.
    Last updated
    9
    MIT
  • A
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    A Python MCP server for note management with RAG capabilities, enabling adding, searching, asking questions, summarizing, and deleting notes, using PostgreSQL and ChromaDB with Google Gemini for embeddings and generation.
    Last updated
    MIT

Matching MCP Connectors

  • Podcast directory search + best podcasts + recommendations via Listen Notes. Free key required.

  • MCP server for Vonage API documentation, code snippets, tutorials, and troubleshooting.

  • Find related notes in Obsidian by analyzing content or keywords to suggest connections for better knowledge organization.
    MIT
  • Retrieves all link relationships for a given note: notes it links to, notes linking to it, and related notes.
    MIT
  • Retrieve LLM-readable documentation for a module, including rules and implementation notes, to guide coding against the module contract.
    MIT
  • Browse notes in a folder with full metadata (tags, type, related, created, modified). Set folder path, optional recursion and limit. Returns detailed note list.
    MIT
  • Discover related concepts in your knowledge library by exploring connections from a note up to a specified depth, returning all reachable notes grouped by distance.
    AGPL 3.0
  • Search Tenzir documentation by keyword to find operators, functions, or concepts, and explore related content through cross-references for comprehensive understanding.
    Apache 2.0
  • Attach private notes to job applications to track thoughts, prep notes, or follow-up reminders. Notes remain visible only to you.
    MIT
  • Retrieve accurate Kubernetes documentation for kubectl commands, API objects, manifests, and version-specific features using a trusted, version-aware index to reduce hallucinations.
    MIT