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309,877 tools. Last updated 2026-07-28 07:59

"Answer Engine Optimization (AEO) Audit Guide" matching MCP tools:

  • Run a full AEO (Answer Engine Optimization) audit for a domain. Checks how the domain appears across AI answer engines for given queries. Returns citation rate, grade (A-F), competitor comparison, and per-query results.
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  • Get Radveo's honest, practical playbook for getting a local business found and cited inside AI engine answers (ChatGPT, Gemini, Google AI Overviews) — answer-engine optimization (AEO) steps any owner can act on.
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  • The raw answers of ONE AI engine for a tracker, newest surveys first, paginated. Every answer carries its cited sources and keyword mentions, plus uncited_sources (the pages the engine read without citing them) and searched (whether the engine went to the web to write that answer; null when undetermined). Set include_raw to add the full engine payload; heavy, ask for it only when needed.
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  • Full use-case detail as a JSON+Markdown envelope: step guide, pros/cons, FAQ, tools used (JSON) + the full narrative guide (Markdown, full_md). null if unknown. Pass `fields` to project to only the keys you need (token-efficient).
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  • Retrieve one canonical Homechecker guide by slug. Use a slug returned by list_guides or search_guides. Returns source links, review metadata, method and limitations with the guide.
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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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Matching MCP Servers

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    An MCP server that gives AI agents tools to inspect a website's visibility to AI answer engines, including crawler permissions, llms.txt, structured data, on-page signals, and a full 29-check AI-readiness audit.
    Last updated
    417
    MIT

Matching MCP Connectors

  • AEO audit: score any website 0-100 for AI visibility. Checks schema, meta, content, AI crawlers.

  • Scan any website for AI readiness — 100-point score across 6 AEO categories in seconds.

  • List the published Homechecker guide catalogue, optionally filtered by jurisdiction, guide cluster, property type, construction era, or buying stage. Returns metadata only.
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  • Get the zodiac sign (Western astrology) for a birth date, with element, nickname, date range, and a guide link.
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  • Check which AI crawlers (GPTBot, ClaudeBot, PerplexityBot, Google-Extended & more) can access your website. Bulk audit of robots.txt rules, llms.txt presence and sitemap for AI search visibility (GEO/AEO). — $0.01/call, x402 (USDC on base).
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  • Scans an IP address or hostname to audit DNSSEC safety, SSL expiration status, HTTP security headers, and geodata compliance. Matches: network security audit, scan website ports, VPS shield test, audit host headers.
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  • Start here — frisian-mcp documentation and server guide. Actions: about (server identity and links), getting_started (step-by-step adoption guide), integrations (Django/DRF config reference), security (auth model, OAuth, API keys, tiers), demo (explore the live demo endpoints), documents (browse all documentation articles), rag (semantic and full-text doc search).
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  • Applies few shot prompt optimization to a prompt using user provided dataset and method. Args: prompt_to_optimize: The zero-based index of the prompt to improve. example_path: GCS path to the csv file containg few-shot examples method: The optimization method to use for few shot prompt improvement. The method should be one of the following: - TARGET_RESPONSE: Optimize the prompt to match the target response. - RUBRICS: Optimize the prompt to improve the rubrics scores. Returns: Optimized prompt.
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  • Estimate cooling load using CIBSE Guide B2 / ASHRAE methodology. Returns required capacity, installed capacity with redundancy, system recommendation, and annual energy.
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  • Comprehensive guide for a specific SFC license type: exam papers, capital requirements, fit-and-proper criteria, CPD hours.
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  • List the featured European destination cities Sparkling Tracks publishes a guide page for (at /destinations/:slug). Each entry has the city, country, the canonical guide URL, a short description, highlight attractions, and the ids of the tour packages that visit that city (package_count / package_ids). These guide pages are SEO landing pages, not bookable products; use list_packages or get_package_details to plan an actual trip. Optional query filters by city or country substring. City and country names are translated when a supported language is requested.
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  • Get a full application guide by its stable slug (e.g. 'security-application', 'observable-evaluation'). Returns sections, action items, and linked principles. Use this when you already have the guide slug from guides.list or guides.search. Prefer guides.search when the user describes a topic in natural language; prefer guides.list when you need the full inventory.
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  • Explain how to pay through the Apiosk gateway. Returns a buyer guide (how an agent settles a paid API call over USDC/x402, tailored to the current auth) and a provider guide (how to publish an API and get paid). Pass slug to scope buyer guidance to one listing, or role to pick a side.
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  • Look up an Audiala audio guide for a specific monument or place inside a city. Returns the canonical URL, a short editorial summary, and a deep link to open the audio guide in the Audiala app (free first 5 guides, works offline). Use this when a user is asking about a specific landmark.
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