Search agent memories by semantic meaning to find relevant information before starting tasks when exact keypaths are unknown.
Apache 2.0
582,781 tools. Updated 2026-09-17 03:55
"Using Google Search to Find Relevant Content" matching MCP tools:
- 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
- Find relevant content across namespaces using natural language queries or vector similarity. Filter results by metadata or keywords for precise discovery.Apache 2.0
- Search the web or Google Drive to find new sources for your research. Pick fast or deep mode to collect relevant sources into a NotebookLM notebook.MIT
- Search the RAG corpus with semantic and keyword hybrid search to find relevant content marketing ideas.MIT
- 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
Matching MCP Servers
- AlicenseAqualityBmaintenanceEnables AI assistants to perform Google searches with real, resolvable sources and transparent search terms.118 npm1MIT
- AlicenseAqualityBmaintenanceMCP server for Google Search using a logged-in browser profile, delivering personalized, ad-free results with advanced operators and pagination. It also fetches web pages as markdown through the same browser session.5MIT
Matching MCP Connectors
google search: google web search api, web, images, videos, news, music, favicon, proxy, audio.
- Content to SocialOAuth
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.
- Search Google News to find articles and news content with automatic topic categorization. Supports multiple languages and countries.MIT
- Find relevant blog posts and essays using semantic search with AI-powered embeddings. Enter a query to retrieve content with relevance scores.MIT
- Search and retrieve relevant VoidFeed content using semantic understanding, returning up to 500 results per query based on tier.MIT
- Search for academic research articles using Google Scholar to find relevant medical and scientific publications for research purposes.MIT
- Search vectorized files in a group using semantic queries to find relevant content based on meaning rather than keywords.MIT
- Search knowledge entries to find relevant insights, tips, and lessons learned. Filter by tags, project, or category to get targeted results.MIT
- Analyzes Google Search Console data to reveal high-potential SEO topics tailored to your niche, audience, and content goals.MIT
- Search across text, audio, and video documents using vector similarity to find relevant content and retrieve full document details.MIT
- Find Google Docs by name using Drive API to locate documents matching your search query within a secure Google Workspace environment.MIT
- Search content across Discourse forums to find relevant topics, posts, and discussions using specific queries.MIT
- Search your Obsidian vault using JsonLogic queries to find notes by content, tags, patterns, or complex criteria for Zettelkasten workflows.MIT
- Search the web for specific information and extract content from results to find relevant data across multiple websites.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
- 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