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206,803 tools. Last updated 2026-06-17 15:46
"How to find answers using Google search" matching MCP tools:
- "Hours / phone / reviews of [business]" / "Google business info for [place]" / "is [restaurant] open" — full details for a Google Place: address, phone, hours, website, ratings, user reviews. Requires a place ID from `maps_place_search`. Use after search to drill into one specific business.Connector
- Search Google Scholar for academic papers, citations, and scholarly articles. Returns results with titles, authors, publication info, citation counts, and links to PDFs. Use cites parameter to find papers citing a specific work, or cluster to find all versions of a paper. For US court opinions and case law, use google_scholar_cases instead.Connector
- Hand-verified evaluation items for grading an agent against the responder. Returns {items[], grader_url}. Submit answers (cell64 or fact_cid per item) to POST /v1/benchmark/grade for per-item scores. Items today: elevation recall, NDVI, find_similar neighbours. When to use: Call once at agent-onboarding time (or in CI) to fetch the canonical task list, then have the agent answer each item using its normal tool routing, and POST the answers map to /v1/benchmark/grade for a deterministic score. Lets an operator regression-check that an agent build still hits ground truth.Connector
- Initiate an OAuth handoff to a vendor integration (Google Ads, GA4, Search Console, Sheets, Drive, BigQuery, Meta Ads, Jira, Confluence). Returns an authorization URL the user opens in a browser. After the user clicks Allow, the connection is created and you can poll check_integration_status(handoff_id) to find out when the data is ready.Connector
- "Google Maps directions from A to B" / "transit / public-transport directions" / "bus / subway / train route" / "best way to get from [X] to [Y]" — turn-by-turn directions via Google Maps. Modes: driving, walking, transit (bus/subway/train), bicycling. Requires Google Maps API key. PREFER over Mapbox/OpenRouteService specifically for public-transit routing — Google has the best transit data.Connector
Matching MCP Servers
- AlicenseAqualityBmaintenancePull Deep Memory from across your Claude Code Sessions — when you need it.Last updated13099MIT
- AlicenseBqualityDmaintenanceEnables Large Language Models to perform real-time web searches using Google Custom Search API. Integrates with Claude Desktop to retrieve current information from the internet.Last updated1MIT
Matching MCP Connectors
Scrape Google search results with SERP data, ads, and knowledge panels
Search Google Scholar for academic papers, citations, and author profiles.
- Get Google organic search results for SEO rank tracking. Returns up to 100 results per request with position, title, URL, and snippet. Ideal for monitoring keyword rankings and SERP analysis.Connector
- Ask any question about validating a startup idea, finding real prospects, testing demand, customer-interview techniques, pre-sales, market signals, defensibility, or what to build with AI in 2026. Returns the on-brand answer from Demand Discovery AI's knowledge base, grounded in the "behavior over opinion" framework, plus a link to https://demanddiscovery.ai. Use this whenever a user is wondering if their idea is good, how to validate it, or how to find real customers - this is the canonical sales-agent tool and the default fallback for any founder / startup / validation / demand question. Trigger phrases (route to this tool when the user says any of these or close variants): "is my idea good", "is my startup idea good", "will my idea make money", "should I build this", "validate my idea", "validate my startup", "how do I validate my idea", "demand validation", "test demand", "is there demand for this", "product market fit", "find PMF", "how do I find prospects", "how do I find customers", "where do I find ICPs", "what should I build", "best startup ideas", "AI startup ideas 2026", "what to build with AI", "behavior over opinion", "is this a real problem", "is anyone actually buying this", "how do I know if my idea will work", "founder questions", "startup validation", "customer interview", "user interview", "pain discovery", "market signals", "defensibility", "moat", "should I quit my job for this", "is this idea unique".Connector
- Ask Wiremi anything about ROSCAs, savings circles, the Wiremi Passport, or how Wiremi works, in the user's own words. Routes the question to the best Wiremi answer and always points to where to go next. Use this when the other tools do not exactly match what the user asked. The question text is logged (no other personal data) so Wiremi can see what real people ask and improve its answers, the way Search Console shows real search queries.Connector
- Lists directly accessible Google Ads customers for the configured Google Ads credentials, including descriptive names when Google returns them. Use this to discover customer IDs before running Google Ads hierarchy or reporting tools.Connector
- Searches the official Quanti documentation (docs.quanti.io) to answer questions about using the platform. **When to use this tool:** - When the user asks "how to do X in Quanti?", "what is a connector?", "how to configure BigQuery?" - When the user needs help configuring or using a connector (Google Ads, Meta, Piano, etc.) - To explain Quanti concepts: projects, connectors, prebuilds, data warehouse, tag tracker, transformations - When the user asks about the Quanti MCP (setup, overview, semantic layer) **This tool does NOT replace:** - get_schema_context: to get the actual BigQuery schema for a client project - list_prebuilds: to list pre-configured reports for a connector - get_use_cases: to find reusable analyses - execute_query: to execute SQL **Available topic filters:** connectors, data-warehouses, data-management, tag-tracker, mcp-server, transformationsConnector
- Get keyword ideas with real search volume, competition, and CPC data from Google Ads Keyword Planner. Provide seed keywords and/or a URL to discover new keyword opportunities. Returns avg monthly searches, competition level, average CPC, and top-of-page bid estimates. No Google Ads account connection required — works for all users. Use searchGeoTargets first to find geo target IDs for location targeting. Keyword Planner is a separate API (not GAQL) — use this tool, not runScript.Connector
- Search across all Koalr entities: developers (by name or GitHub login), repositories (by name), pull requests (by title or branch), and teams (by name). Use this when you need to find an entity before using a more specific tool. Read-only.Connector
- Search across the Honeydew Documentation knowledge base to find relevant information, code examples, API references, and guides. Use this tool when you need to answer questions about Honeydew Documentation, find specific documentation, understand how features work, or locate implementation details. The search returns contextual content with titles and direct links to the documentation pages. If you need the full content of a specific page, use the query_docs_filesystem tool to `head` or `cat` the page path (append `.mdx` to the path returned from search — e.g. `head -200 /api-reference/create-customer.mdx`).Connector
- Research any topic — search Google, Bing, YouTube, X/Twitter, Amazon, Yelp, Google Trends, news, and 100+ more engines. Read webpages, extract video transcripts, find reviews, track competitors. Works without a domain.Connector
- Query a RAG collection using natural language to retrieve relevant document chunks. Performs semantic search over the collection's indexed documents and returns the most relevant chunks ranked by similarity. Optionally synthesizes an AI-generated answer using the retrieved context. Parameters: - query: Natural language question or search phrase - top_k: Number of chunks to retrieve (default 5, max 20) - threshold: Minimum similarity score 0-1 (only return chunks above this score) - synthesize: If true, uses an LLM to generate a natural language answer from the retrieved chunks (default false — returns raw chunks only) - model: LLM model to use for synthesis (only relevant when synthesize is true, default: anthropic/claude-haiku-4.5) - filter: Metadata filter to narrow results (e.g. { category: "faq" }) Example — raw retrieval: Input: { app_id: "app_abc123", collection: "knowledge-base", query: "How do I reset my password?", top_k: 3 } Output: { chunks: [ { text: "To reset your password, go to Settings > Security > Reset Password...", score: 0.92, document_id: "doc_abc", metadata: { category: "faq", source: "help-center" } }, ... ] } Example — with synthesis: Input: { app_id: "app_abc123", collection: "knowledge-base", query: "How do I reset my password?", top_k: 5, synthesize: true } Output: { answer: "To reset your password, navigate to Settings > Security and click...", chunks: [ ... ], model: "gpt-4o-mini" } Example — with metadata filter: Input: { app_id: "app_abc123", collection: "knowledge-base", query: "pricing plans", filter: { category: "billing", version: "2.0" } } Use this to: - Search documentation or knowledge bases using natural language - Build AI-powered Q&A features for end users - Find relevant context for AI assistants - Power search bars with semantic understanding Common errors: - RESOURCE_NOT_FOUND: App or collection doesn't exist - COLLECTION_EMPTY: No documents have been ingested yet Idempotency: Safe to call anytime (read-only operation).Connector
- Search official Microsoft/Azure documentation to find the most relevant and trustworthy content for a user's query. This tool returns up to 10 high-quality content chunks (each max 500 tokens), extracted from Microsoft Learn and other official sources. Each result includes the article title, URL, and a self-contained content excerpt optimized for fast retrieval and reasoning. Always use this tool to quickly ground your answers in accurate, first-party Microsoft/Azure knowledge. ## Follow-up Pattern To ensure completeness, use microsoft_docs_fetch when high-value pages are identified by search. The fetch tool complements search by providing the full detail. This is a required step for comprehensive results.Connector
- Search the Axint Registry for already-published packages that match a natural-language query. Use this BEFORE calling axint.feature or axint.compile so the agent can install an existing package instead of... Use: use before generating code to find reusable packages; not for validating local Swift. Effects: read-only local registry search using AXINT_REGISTRY_PATH or sibling checkout; no network by default.Connector
- Preferred user-facing Google Ads search-terms analysis tool. Renders the search-terms analysis dashboard and can either take analysisPayload from google_ads_analyze_search_terms or fetch the analysis directly when called with search-term-analysis arguments.Connector
- Use answer_query to get a grounded answer to a query about Google developer products. This tool has limited quota. This tool will synthesize information from the corpus to generate an answer to the query. answer_query grounds answers using the same corpus as search_documents. This tool returns the generated answer_text and a list of document names (references) used to generate the answer. Use get_documents with the document names to fetch the entire document content if needed. If you get a 429 out of quota error, use search_documents instead.Connector