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
331,141 tools. Last updated 2026-07-29 14:20
"Using Google Search to Find Relevant Content" matching MCP tools:
- Search agent memories by semantic meaning to find relevant information before starting tasks when exact keypaths are unknown.Apache 2.0
- Find relevant content across namespaces using natural language queries or vector similarity. Filter results by metadata or keywords for precise discovery.Apache 2.0
- Use natural language queries to semantically search video collections and find relevant videos based on content, summaries, and metadata. Returns results with relevance scores.MIT
- Perform real-time web searches and scrape content from URLs using AI-powered search. Configure result counts and search depth to find relevant information.MIT
- Search and retrieve relevant VoidFeed content using semantic understanding, returning up to 500 results per query based on tier.MIT
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Matching MCP Connectors
Transform any blog post or article URL into ready-to-post social media content for Twitter/X threads, LinkedIn posts, Instagram captions, Facebook posts, and email newsletters. Pay-per-event: $0.07 for all 5 platforms, $0.03 for single platform.
Scrape Google search results with SERP data, ads, and knowledge panels
- Search for academic research articles using Google Scholar to find relevant medical and scientific publications for research purposes.MIT
- Search academic papers on Google Scholar by query, author, or publication year to find relevant research publications.MIT
- Search content across Discourse forums to find relevant topics, posts, and discussions using specific queries.MIT
- Search HEPData records using native search syntax to find relevant datasets and tables.GPL 2.0
- Search your Obsidian vault using JsonLogic queries to find notes by content, tags, patterns, or complex criteria for Zettelkasten workflows.MIT
- Initiate web or Google Drive searches to find new sources for research topics. Choose between fast or deep search modes to gather relevant information for your notebook.MIT
- Search the web for specific information and extract content from search results to find relevant data.MIT
- Retrieve Google AI Overview results by using the follow-up URL provided in a Google Search API response, returning structured text blocks and references.MIT
- Search for content within Scrapbox project pages using keywords, phrases, or advanced operators to find relevant information quickly.MIT
- Find OneDrive documents using semantic and keyword hybrid search to discover relevant files by topic when exact names are unknown. Returns file metadata, previews, and URLs for analysis.MIT
- Browse knowledge collections with document counts, or perform semantic search to find relevant collections.MIT
- Search OpenTelemetry documentation to find relevant pages when you don't have a specific URL. Use technical terms and OpenTelemetry concepts to improve search results.Apache 2.0
- Search Turkish Presidential Decisions using keyword Boolean operators or semantic queries to find relevant content from PDF-based documents.MIT
- Search the Segnals knowledge base using semantic search to find help articles, feature documentation, and trading guides.MIT