"A server for finding food reviews and restaurant recommendations on Dianping" matching MCP tools:

• search_reviews

  Cochrane Medical Reviews

  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).

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• find_similar_products

  market

  Given a product ID, find similar products across the entire catalog. Useful for "more like this" recommendations or finding alternatives. Returns compact product cards, not full variant detail; call get_product for SKU-level variants, exact variant prices, merchant description, store info, and all images. Returns page and hasNextPage. Returns up to 20 results per page, paginated (max 3 pages).

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• get_food_environment

  USDA Food Access

  Get county-level food access risk profiles using Census ACS data. Constructs food access risk profiles by combining vehicle access (B25044), poverty status (B17001), and SNAP participation (B22001). Limited vehicle access combined with high poverty indicates food desert risk. Useful for identifying areas with barriers to food access in grant applications. Args: state: Two-letter state abbreviation (e.g. 'WA', 'MS') or 2-digit FIPS code. county_fips: Three-digit county FIPS code (e.g. '033' for King County, WA). Omit to get all counties in the state.

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• tourradar_vertex-review-search

  MolTravel

  [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.

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• hasdata_google_maps_photos_getMapPhotos

  HasData

  Get Place Photos Fetches the photo gallery of a Google Maps place by dataId or placeId, paginated with nextPageToken and filterable by categoryId (all, latest, menu, by owner, videos, street view). Returns each photo with image URL, thumbnail, upload date, uploader, and photoId. Use for restaurant-menu extraction, venue/ambience visual audits, building rich place detail pages, and sourcing up-to-date imagery for POI listings.

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• search_sic_codes

  SIC Codes UK

  Search for UK SIC 2007 codes by business activity description. Describe what a business does in plain English and get ranked SIC code recommendations with relevance scores, hierarchy breadcrumbs, and GICS/ICB cross-classification mappings. Useful for finding the right SIC code for Companies House registration.

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• get_top_funding_rates

  MarketMCP

  Top Hyperliquid perps ranked by absolute funding rate, with OI and annualized yield. Useful for finding the most overcrowded longs/shorts and carry opportunities.

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• search_sic_codes

  SIC Codes UK

  Search for UK SIC 2007 codes by business activity description. Describe what a business does in plain English and get ranked SIC code recommendations with relevance scores, hierarchy breadcrumbs, and GICS/ICB cross-classification mappings. Useful for finding the right SIC code for Companies House registration.

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• nanmesh.trust.review

  NaN Mesh

  Cast your expert +1 or -1 review on any entity. Use AFTER evaluating a tool you searched for or tried. Expert reviews are 70% of ranking. One review per agent per entity (overwrites previous). Requires agent_key. For no-auth alternative, use nanmesh.trust.favor instead. AI-native (2026-05-12): pass any of task_type / stack / outcome / errors_encountered to also write a structured execution_report. Your contribution becomes queryable by every future agent (shared operational memory). Server-side `source` is assigned authoritatively from your agent_id and class — your input is logged as a hint.

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• originators_like

  Quotewise

  Find originators similar to the given one using vector similarity (quote themes). Use after finding an author to discover related thinkers. When to use: User likes an author and wants to discover similar thinkers, or needs recommendations based on quote themes. Returns originators with similarity scores (0-100%). Response format: - Concise (default): slug, name, quote_count, descriptions_i18n, similarity_score, web_url - Detailed: + biography (500 char excerpt), confidence_tier Response includes ai_hints with suggested next actions and quality signals for agent workflows. Examples: - `originators_like(originator="Marcus Aurelius")` - similar philosophers - `originators_like(originator="Oscar Wilde")` - similar wits - `originators_like(originator="African Proverbs")` - similar proverb collections

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• getProductDetails

  dm-drogerie-markt

  Retrieve detailed product information for dm-drogeriemarkt products. USE WHEN: ingredients, nutrition facts, allergens, usage instructions, warnings, hazard info, product URLs/images INPUT: DANs (7 digits, preferred) and/or GTINs (8-14 digits) multiple products can be requested at once min 1 / max 50. Use search tool first if only product name is known. OUTPUT: TOON format (compact YAML-like). Fields: name, brand, description, ingredients, nutrition, allergens, usage, warnings, URLs, images. found=false for unresolved IDs. NOT FOR: prices, availability, stock, reviews, recommendations ERRORS: validation error if >50 or no identifiers

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• search_local_businesses

  google-maps-mcp-server

  Search Google Maps for local businesses matching a query and location. Returns business name, complete address, star rating, review count, phone number, website URL, and business category. Use for restaurant discovery, service provider lookup, or competitive local analysis. Returns open/closed status.

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• recipes_collections

  SAVORDISH

  Browse curated recipe collections by theme — date night, comfort food, quick weeknight, party appetizers, and more. TRIGGERS: - 'date night recipes', 'comfort food ideas', 'party appetizers' - 'meal prep recipes', 'one pot meals', 'kid-friendly recipes' - 'romantic dinner', 'game day food', 'brunch ideas'

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• markets-screener

  USDV Capital — Your Real Estate CFO

  Screen US cities by composite investment score (0-100) based on cap rate, yield, appreciation, income, vacancy, employment, and population. Pre-computed for 18,800+ cities. Ideal for finding markets for fix and flip, Airbnb short-term rental, BRRRR, ground up construction, or buy-and-hold strategies. USDV Capital — Your Real Estate CFO.

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• fda_search_debarments

  FDA Data MCP

  Search current FDA debarment lists across drug applications, drug imports, and food imports. These are rare but very high-severity compliance signals for people or firms barred from certain FDA-regulated activities.

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• aws___recommend

  AWS Knowledge

  Get content recommendations for an AWS documentation page. ## Usage This tool provides recommendations for related AWS documentation pages based on a given URL. Use it to discover additional relevant content that might not appear in search results. URL must be from the docs.aws.amazon.com domain. ## Recommendation Types The recommendations include four categories: 1. **Highly Rated**: Popular pages within the same AWS service 2. **New**: Recently added pages within the same AWS service - useful for finding newly released features 3. **Similar**: Pages covering similar topics to the current page 4. **Journey**: Pages commonly viewed next by other users ## When to Use - After reading a documentation page to find related content - When exploring a new AWS service to discover important pages - To find alternative explanations of complex concepts - To discover the most popular pages for a service - To find newly released information by using a service's welcome page URL and checking the **New** recommendations ## Finding New Features To find newly released information about a service: 1. Find any page belong to that service, typically you can try the welcome page 2. Call this tool with that URL 3. Look specifically at the **New** recommendation type in the results ## Result Interpretation Each recommendation includes: - url: The documentation page URL - title: The page title - context: A brief description (if available)

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• get_snap_participation

  USDA Food Access

  Get SNAP/food stamp household participation by county using Census ACS Table B22001. Returns the number and percentage of households receiving vs not receiving SNAP/food stamp benefits, broken down by county. Essential for understanding food assistance utilization in grant target areas. Args: state: Two-letter state abbreviation (e.g. 'WA', 'MS') or 2-digit FIPS code. county_fips: Three-digit county FIPS code (e.g. '033' for King County, WA). Omit to get all counties in the state. year: ACS 5-year estimate year (default 2022). Data covers year-4 through year.

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• thinkneo_registry_review

  ThinkNEO Control Plane

  Rate and review an MCP server in the ThinkNEO Marketplace. One review per user per package (updates on repeat). Rating from 1 (poor) to 5 (excellent) with optional comment. Reviews affect the package average rating shown in search results. One review per user per package (updates on repeat). Authentication required.

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• get_failing_checks

  Waivern Cookie Consent Analyser

  Return only the FAIL and PARTIAL checks from a completed scan. This is the most useful tool for an agent writing a compliance summary or remediation plan — it omits all the passing checks and focuses entirely on what needs to be fixed, with actionable recommendations for each issue.

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• hasdata_google_maps_reviews_getMapReviews

  HasData

  Get Map Reviews Paginated fetch of Google Maps reviews for a place by dataId or placeId, with sort (qualityScore, newestFirst, ratingHigh, ratingLow), topicId filter, and language. Returns per-review author name and profile link, star rating, text, published/relative date, likes count, owner response, attached photos, and local-guide flag. Use for reputation management, sentiment and topic mining, competitor review benchmarking, and feeding review data into summarization or trust-score LLMs.

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