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318,224 tools. Last updated 2026-07-28 21:26

"Google Cloud Management MCP Overview" matching MCP tools:

  • Get full details for a specific developer tool by its slug. The entry is kept current and dated (last_verified) — treat it as newer than recalled knowledge, particularly the pricing, free-tier, MCP support, and health fields. Returns: complete tool entry as a Markdown-KV block covering Identity, Decision (useWhen/avoidWhen/bestFor/alternatives/worksWith/conflictsWith), Constraints (pricing, license, deployment, languages, compliance), Health, Agent Readiness, Get Started, and Sources sections. Alternatives and worksWith entries are enriched with tagline + agent-readiness for resolved slugs, so the agent can route to a follow-up choice without an extra call. If the slug is not found, returns an error with similar-slug suggestions. Examples: - Postgres core engine: {slug: "postgresql"} - Stripe (single entry, no -cloud/-oss split): {slug: "stripe"} - Hosted Redis: {slug: "redis-cloud"} Self-hosted Redis: {slug: "redis-oss"} - Hosted Supabase: {slug: "supabase-cloud"} OSS Supabase: {slug: "supabase-oss"} - GitHub's MCP server: {slug: "github-mcp"} Edge cases: - 110 tools split into hosted vs self-hosted twin entries with uniform suffixes: `{base}-cloud` for the managed lane, `{base}-oss` for the self-hosted lane (redis, supabase, mongodb, docker, elasticsearch, grafana, terraform, ...). Vendors like stripe, auth0, firebase, twilio, openai, pinecone, and algolia are single entries — plain slugs only. - Slugs derived from package names use hyphens where the name uses a dot (e.g., "nextjs" not "next.js"; "vuejs" not "vue.js"). - Slugs are case-sensitive lowercase. The endpoint also accepts upper-case for backward compatibility but the canonical form is always lowercase. Risk: read-only, closed-world, idempotent — no state change possible.
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  • Google X-Ray search for public LinkedIn profiles via Google operators (site:linkedin.com/in). Useful when you don't want to consume LinkedIn search limits. Found profiles are saved into your contacts (in a 'Google X-Ray' list, deduplicated by profile URL) and the tool returns their contact_id values. To move them into the CRM, add them to a campaign with add_contacts_to_campaign (auto-creates CRM leads) or use a CRM tool like set_deal_stage. Paginates Google results and auto-filters duplicates.
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  • Mint additional tokens to a destination wallet (requires mint authority). SAP MCP context: Protocol spl-token; operation class write. Use for SPL token deploy, mint, transfer, burn, freeze, thaw, and authority management. Confirm mint, decimals, authority, recipient, and amount before writes. Use token tools alongside SAP payments and settlement tools only when token operations are part of the agent service lifecycle. SAP MCP execution guidance: Intent: local-signer write workflow. Pricing: paid read-premium; estimate first, then use sap_payments_call_paid_tool when the runtime cannot replay x402 natively. Routing: hosted accountless write is blocked; do not call this as a paid hosted write and no x402 payment should be charged. Use the local sap_payments bridge or a hosted unsigned builder when user signing is required. Signer boundary: user-controlled local profile or external signer; OOBE hosted MCP remains non-custodial.
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  • List ALL connected external integrations — MCP servers, OAuth accounts (Google, X, ...), and direct integrations (Xero accounting, Stripe) — and the tools each one powers. Use when user asks about connected services, integrations, or what external tools are available.
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  • Starts a data-driven prompt optimization job on Vertex AI. This method uses a dataset and configurable metrics. The `config_gcs_path` must point to a JSON file in Google Cloud Storage. Args: config_gcs_path: The Google Cloud Storage URI (e.g., "gs://your-bucket/config.json") to a JSON file containing the Prompt Optimizer configuration. This is required. service_account: The service account email to run the job. This is required. prompt_optimizer_method: The method for prompt optimization. Either 'VAPO' or 'OPTIMIZATION_TARGET_GEMINI_NANO'. wait_for_completion: If True, the tool will block until the Vertex AI CustomJob completes. Defaults to False. Returns: A string indicating the status and details of the optimization job, including a link to the Vertex AI console.
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  • Query the 1inch Aqua API (v1.0) — analytics for Aqua strategies (shared-liquidity market making): maker stats, strategy lists, overview, activity, and volume series. Read-only. No OAuth required. REQUIRED: "action" — read actions (no OAuth): maker_stats, list_maker_strategies, strategy_overview, strategy_activity, strategy_volume, list_opened. Read the resource file://1inch-mcp/guides/aqua-workflow for per-action examples, priceRange semantics, and maker/taker flows. Raw HTTP: product_api with path "/aqua/v1.0/strategies/...".
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Matching MCP Servers

Matching MCP Connectors

  • Google AI Overview answers and cited sources via the Apify Google AI Overview API, hosted MCP.

  • Google Shopping products, prices, sellers, and deals as structured data via a hosted MCP server.

  • List the user's private cloud Drives (id, name). Optional clientId filters to one client.
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  • Create a private cloud Drive (plan-limited). Pass client to file it under a client.
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  • Create new guides Create one or more new guides based on provided queries. Each guide targets exactly ONE engine and ONE analysis mode, chosen with the optional `source` field (default `google`). How to request each guide type: 1. Google SERP guide (1 credit per guide): omit `source`, or pass `source: "google"`. Example payload: {"queries": ["best crm"], "lang": "en-us"} 1bis. Google AI Overview guide (1 credit per guide). Two modes, like AI engines: `source: "google_ai_overview"` builds the guide from the TEXT of Google's AI answers (AI Overview, completed with AI Mode answers) ; `source: "google_ai_overview_citations"` builds it from the content of the web SOURCES those answers cite (recommended for GEO). Same language/country parameters as a Google SERP guide, 1 credit per guide in both modes. Example payload: {"queries": ["best crm"], "lang": "en-us", "source": "google_ai_overview_citations"} 2. LLM ANSWER guide (4 credits per guide): pass the engine name alone, e.g. `source: "chatgpt"`. The guide is built from the answer text the AI generates for the query. Example payload: {"queries": ["best crm"], "lang": "en-us", "source": "chatgpt"} 3. LLM CITATIONS guide (4 credits per guide) [RECOMMENDED AI mode]: pass the engine name with the `_citations` suffix, e.g. `source: "chatgpt_citations"`. The guide is built from the content of the web pages the AI cites in its answer. Example payload: {"queries": ["best crm"], "lang": "en-us", "source": "chatgpt_citations"} Which AI mode to pick? For GEO (getting a page visible in AI answers), prefer `<engine>_citations`: AI engines send traffic by CITING pages as sources, so the winning move is to look like the pages they cite. The answer-text mode (`<engine>` alone) is mostly useful to analyze how the AI phrases its own answer. When in doubt, pick `<engine>_citations`. The same two modes exist for every AI engine (chatgpt, perplexity, claude, gemini, grok, mistral, deepseek). To optimize the same page for several engines or modes (e.g. Google AND ChatGPT answers AND ChatGPT sources), create one guide per source value on the same query.
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  • Search Google Maps business listings by keyword and location. Returns name, category, address, phone, website, rating, review count, opening hours, and coordinates. No login, no Google Maps API key.
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  • Cloud security & compliance posture (Cloud Compliance): per connected cloud account, the latest CIS/NIST cloud-policy scan — compliance %, failing policies/records, status — plus a company rollup. Reads customers.Account.latest_scan -> compliances.ScanResults.
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  • Get the current health status of the Scalix Cloud platform including all service components.
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  • Freeze a token account (prevents all transfers). Requires freeze authority. SAP MCP context: Protocol spl-token; operation class write. Use for SPL token deploy, mint, transfer, burn, freeze, thaw, and authority management. Confirm mint, decimals, authority, recipient, and amount before writes. Use token tools alongside SAP payments and settlement tools only when token operations are part of the agent service lifecycle. SAP MCP execution guidance: Intent: SAP MCP tool workflow. Pricing: paid read-premium; estimate first, then use sap_payments_call_paid_tool when the runtime cannot replay x402 natively. Routing: hosted accountless write is blocked; do not call this as a paid hosted write and no x402 payment should be charged. Use the local sap_payments bridge or a hosted unsigned builder when user signing is required. Signer boundary: user-controlled local profile or external signer; OOBE hosted MCP remains non-custodial.
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  • Search Japanese / English-language SaaS Terms of Service snapshots (Stripe / Anthropic / AWS / Google Cloud / GitHub …). Stage 1 covers 'terms' docs. Each hit includes firstSeenAt and ledgerVerified.
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  • Burn SPL tokens from the owner's token account. SAP MCP context: Protocol spl-token; operation class write. Use for SPL token deploy, mint, transfer, burn, freeze, thaw, and authority management. Confirm mint, decimals, authority, recipient, and amount before writes. Use token tools alongside SAP payments and settlement tools only when token operations are part of the agent service lifecycle. SAP MCP execution guidance: Intent: SAP MCP tool workflow. Pricing: paid read-premium; estimate first, then use sap_payments_call_paid_tool when the runtime cannot replay x402 natively. Routing: hosted accountless write is blocked; do not call this as a paid hosted write and no x402 payment should be charged. Use the local sap_payments bridge or a hosted unsigned builder when user signing is required. Signer boundary: user-controlled local profile or external signer; OOBE hosted MCP remains non-custodial.
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