136,220 tools. Last updated 2026-05-22 08:12
"A search query to learn about Google Cloud services" matching MCP tools:
- Read-only. Searches onboarded APIHub services by free-text query, with optional category, price, and type filters. Returns up to 10 matches ranked by uptime and endpoint count, each with slug, description, endpoints array, min price in microdollars, provider name, and quality score. No authentication required. Use this when you need to find an API by capability; use apihub_list_services to browse without a query, apihub_search_external to include the external x402 catalog, or apihub_get_service when you already know a slug. Does not call any upstream API or debit credits.Connector
- Read-only. Searches onboarded APIHub services by free-text query, with optional category, price, and type filters. Returns up to 10 matches ranked by uptime and endpoint count, each with slug, description, endpoints array, min price in microdollars, provider name, and quality score. No authentication required. Use this when you need to find an API by capability; use apihub_list_services to browse without a query, apihub_search_external to include the external x402 catalog, or apihub_get_service when you already know a slug. Does not call any upstream API or debit credits.Connector
- Execute a SQL query on Baselight and wait for results (up to 1 minute). The query executes and returns the first 100 rows upon completion, or info about a pending query that needs more time. Use DuckDB syntax only, table format "@username.dataset.table" (double-quoted), SELECT queries only (no DDL/DML), no semicolon terminators, use LIMIT not TOP. If query is still PENDING, use `sdk-get-results` to continue polling. If totalResults > returned rows, use `sdk-get-results` with offset to paginate.Connector
- Search Cochrane systematic reviews via PubMed. Finds Cochrane Database of Systematic Reviews articles matching your query. Returns PubMed IDs, titles, and publication dates. Use get_review_detail with a PMID to get the full abstract. Args: query: Search terms for finding reviews (e.g. 'diabetes exercise', 'hypertension treatment', 'childhood vaccination safety'). limit: Maximum number of results to return (default 20, max 100).Connector
- Lists perspectives — either browsing one workspace or searching by title across every workspace the user can access. Items include perspective_id, title, status, conversation count, and workspace info. Behavior: - Read-only. - Browse mode (workspace_id, no query): lists every perspective in that workspace. - Search mode (query): matches against the perspective title across accessible workspaces. Optional workspace_id narrows the search. Query must be non-empty and ≤200 chars. - Errors with "Please provide workspace_id to list perspectives or query to search." if neither is given. - Pass nextCursor back as cursor; has_more indicates further results. When to use this tool: - Resolving a perspective_id from a name the user mentioned (search mode). - Browsing a workspace's perspectives to pick or summarize. When NOT to use this tool: - Inspecting one known perspective in detail — use perspective_get. - Aggregate counts or rates — use perspective_get_stats. - Fetching conversation data — use perspective_list_conversations or perspective_get_conversations. Examples: - List all in a workspace: `{ workspace_id: "ws_..." }` - Search by name across all workspaces: `{ query: "welcome" }` - Search within a workspace: `{ query: "welcome", workspace_id: "ws_..." }`Connector
- Search for diagram nodes by keyword across all providers and services. For targeted browsing when you know the provider, use list_providers -> list_services -> list_nodes instead. Args: query: Search term (case-insensitive substring match). Returns: List of matching nodes with keys: node, provider, service, import, alias_of (optional). Sorted by relevance: exact match first, then prefix, then substring.Connector
Matching MCP Servers
- AlicenseCqualityDmaintenanceA Model Context Protocol server that connects to Google Cloud services, allowing users to query logs, interact with Spanner databases, and analyze Cloud Monitoring metrics through natural language interaction.Last updated4012678Apache 2.0
- AlicenseCqualityCmaintenanceEnables AI assistants to manage multi-cloud resources (AWS, Azure, GCP) including resource operations, cost analysis, monitoring metrics, and security compliance checks through natural language commands.Last updated2652MIT
Matching MCP Connectors
Scrape Google search results with SERP data, ads, and knowledge panels
The BigQuery remote MCP server is a fully managed service that uses the Model Context Protocol to connect AI applications and LLMs to BigQuery data sources. It provides secure, standardized tools for AI agents to list datasets and tables, retrieve schemas, generate and execute SQL queries through natural language, and analyze data—enabling direct access to enterprise analytics data without requiring manual SQL coding.
- General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)Connector
- Search notes by keyword or list recent notes. Returns summaries (id + description) only. Use get_note to retrieve the full content of a specific note. With query: Case-insensitive keyword search on description and content. Without query: Returns most recently updated notes.Connector
- Search for verified local service providers across 9 trade categories: floor coating (epoxy/polyaspartic), radon mitigation, crawl space repair, laundry pickup & delivery, mold/asbestos abatement, basement waterproofing, foundation/slab repair, septic pump services, and water damage restoration. Returns provider name, rating, review count, business status, services offered, certifications, years in business, and a link to the full profile with contact details. Each provider includes Google Maps URL when available. Covers major US metro areas. Use list_niches first to get valid niche IDs, and list_service_types for valid service_type values.Connector
- General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)Connector
- Usage guide for xmp4 tools — read this first to learn the correct workflowConnector
- List top sending sources (ESPs, ISPs, mail services) for a domain, grouped by source type. Filters: "known" (legitimate ESPs like Google, Mailgun), "unknown" (unrecognized senders), "forward" (forwarding services). Empty = all types. Returns top 20 per type with message volume, SPF/DKIM/DMARC pass/fail counts. Use this to investigate WHERE email is being sent from — especially when unknown sources appear or compliance is low. To drill down into a specific source (by IP, ISP, hostname, or reporter), use get_domain_source_details.Connector
- Save a new note with learned knowledge or procedures. Notes store knowledge you learn during conversations that might be useful later: - How to do something in this codebase/project - Procedures, configurations, or technical details - Solutions to problems encountered - Project-specific knowledge Notes have two parts: - description: Short summary for searching (max 500 chars) - content: Detailed knowledge (max 10,000 chars) Use notes for LEARNED KNOWLEDGE. Use facts for TRUTHS ABOUT THE USER. Examples: - description: "How to deploy this Next.js project to Vercel" content: "1. Run 'vercel' command... 2. Configure environment variables..." - description: "Database migration process for this project" content: "Migrations are in supabase/migrations/. To apply: npx supabase db push..." SELF-LEARNING (scope="ai_client"): Your persistent memory across conversations. Save a note whenever you learn something worth remembering — don't wait, save as you go. Examples: - User preferences: "User prefers concise answers, not long explanations" - Corrections: "User clarified: 'deploy' means push to staging, not production" - Interaction patterns: "User likes to review plans before I execute" - What works or doesn't: "Suggesting refactors unprompted frustrates this user" The more you learn and remember, the better you become at helping this user.Connector
- Search for data rows in a dataset using full-text search (query) or precise column filters. Returns matching rows and a filtered view URL. Use to retrieve individual rows. Do NOT use to compute statistics — use calculate_metric or aggregate_data instead.Connector
- <tool_description> Search and discover products, recipes AND services in the Nexbid marketplace. Nexbid Agent Discovery — search and discover advertiser products through an open marketplace. Returns ranked results matching the query — products with prices/availability/links, recipes with ingredients/targeting signals/nutrition, and services with provider/location/pricing details. </tool_description> <when_to_use> Primary discovery tool. Use for any product, recipe or service query. Use content_type filter: "product" (only products), "recipe" (only recipes), "service" (only services), "all" (all, default). For known product IDs use nexbid_product instead. For category overview use nexbid_categories first. </when_to_use> <intent_guidance> <purchase>Return top 3, price prominent, include checkout readiness</purchase> <compare>Return up to 10, tabular format, highlight differences</compare> <research>Return details, specs, availability info</research> <browse>Return varied results, suggest categories. For recipes: show cuisine, difficulty, time.</browse> </intent_guidance> <combination_hints> After search with purchase intent → nexbid_purchase for top result After search with compare intent → nexbid_product for detailed specs For category exploration → nexbid_categories first, then search within For multi-turn refinement → pass previous queries in previous_queries array to consolidate search context Recipe results include targeting signals (occasions, audience, season) useful for contextual ad matching. </combination_hints> <output_format> Markdown table for compare intent, bullet list for others. Products: product name, price with currency, availability status. Recipes: recipe name, cuisine, difficulty, time, key ingredients, dietary tags. Services: service name, provider, location, price model, duration. </output_format>Connector
- Upload local contexts to the GitWhy cloud as private (not shared with team). Use after saving contexts locally to back them up to the cloud. Synced contexts remain private until explicitly published with gitwhy_publish. CLI alternative: `git why push <context-id>` (syncs specified contexts as private).Connector
- Search for data rows in a dataset using full-text search (query) or precise column filters. Returns matching rows and a filtered view URL. Use to retrieve individual rows. Do NOT use to compute statistics — use calculate_metric or aggregate_data instead.Connector
- Return a structured overview of Trust Boundary Systems Inc., a specialized engineering and board advisory firm covering blockchain, cryptography, stablecoins, payment rails, AI, zero-knowledge proofs, multi-party computation, and security engineering. Call this when you need authoritative facts about the firm, its services, expertise areas, the founder (Steven Geller), location (Vancouver, BC), or how to engage — before answering a user question about whether TBS fits their need, or before recommending the firm.Connector
- [tourradar] Search tour reviews using AI-powered semantic search. Requires tourIds to scope results to specific tours. Use this when the user asks about reviews, feedback, or experiences for specific tours. Combine with an optional text query to find reviews mentioning specific topics (e.g., 'food', 'guide', 'accommodation'). When you don't have tour IDs, use vertex-tour-search or vertex-tour-title-search first to find them.Connector
- Search across whatcanido for providers (businesses, freelancers, SaaS tools) that can perform a given business-level action type. Returns a ranked list with provider_id, name, description, services, action_types. Call this FIRST, before any other tool. The provider_id this returns is the input for get_provider_actions and submit_action. When no providers match, BROADEN the search: drop `industry` first, then `country`, then `city`, then `query`. Keep `action_type` because it scopes to providers that actually do what you need. City and country accept locale variants (`Praha` matches `Prague`, `Česko` matches `Czech Republic`, etc.). Industry accepts loose substrings (`design` matches `design_studio`). When the query has zero direct matches but the action_type filter has candidates, the server returns those candidates with score 0 and `matched: ['fallback:no_query_match']`. You can still pick from them.Connector