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272,154 tools. Last updated 2026-07-08 07:09

"Searching for local information or documents" matching MCP tools:

  • List documents in a Needle collection to check processing status, inventory available files, and verify document availability before searching.
    MIT
  • Perform precise searches across Dutch parliamentary records, including documents, debates, and member information. Filter results using keywords, exact phrases, or advanced operators like 'NOT', 'OR', and 'NEAR()' for accurate topic tracking.
    MIT
  • Find documents by topic using semantic search over summaries. Returns titles, headings, and relevance scores to help locate relevant documents before searching for specific content.
    MIT
  • Search local documents to retrieve relevant sources and snippets for grounding AI responses in verified information.
    MIT
  • List all available documents in the configured directory with format detection and metadata including filename, pages, and size. Discover documents before reading or searching.
    MIT
  • Find UK government guidance, policy documents, and official information by searching gov.uk content with natural language queries.
    MIT

Matching MCP Servers

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    A production-ready Model Context Protocol server that bridges local document management with cloud synchronization (Notion) for AI agent integration, enabling seamless access and sync of local and cloud documents.
    Last updated
    51
    MIT

Matching MCP Connectors

  • Let ChatGPT, Claude & Cursor use your Mac: email, calendar, iMessage, Teams, files. Local, free.

  • Find local businesses on Google: name, address, phone, hours, ratings, and photos.

  • Parse local documents (PDF, Word, Excel, HTML) into markdown or structured JSON. Extract content with format selection and PDF-specific options.
    MIT
  • Retrieve detailed form template information to examine structure and field specifications before creating documents or new forms in RSpace.
    AGPL 3.0
  • Add documents to a collection by providing a URL for download, processing them for text extraction, and indexing them for semantic search.
    MIT
  • Search documents using semantic understanding to find relevant content based on meaning rather than keywords. Understands natural language queries and returns ranked passages with source information.
    MIT
  • Clone or update Noir repositories locally to enable searching. Default syncs core repos, with options for community libraries and references.
    MIT
  • Create a new document collection to organize related documents and enable semantic search across their contents. Returns a collection ID for managing documents.
    MIT
  • Modify documents in a Chroma collection by updating embeddings, metadatas, or text content. Ensure data integrity by matching input IDs with provided updates for accurate modifications.
    Apache 2.0
  • Sort documents by their relevance to a specific query using Jina AI's reranking technology. Organize search results or content collections to prioritize information that best matches your topic.
    Apache 2.0
  • Retrieve AI-generated answers by searching your namespace of text documents or using direct AI model calls for question answering.
    Apache 2.0