"A server for finding food outlets near me" matching MCP tools:

• cyanheads_describe

  cyanheads-mcp-server

  Return the description and install snippets for a named tool or server. For tools: the description and the server it belongs to. For servers: local (stdio, via npx) install snippets for every published server, plus remote (HTTP) connection snippets when a hosted endpoint exists — for every supported client, or one client via the client parameter. Call cyanheads_search first to find valid names.

  Connector

• show_media

  switch

  Display the user's images inline — one or many. Users speak plainly and will NOT know asset ids; never ask for one, resolve it yourself. For "show me" or "show me my last image" call with NO arguments (shows the most recent image). For "show me my last 4 images / my last 10 pictures" pass count=N (returns a clean grid, up to 12). For a specific known image pass assetId. Renders a branded SwitchApp media card with a Download action per result; do not just print URLs. (Videos are not shown here — use list_my_videos and return the newest finished video's view_url, which plays.)

  Connector

• check_allergens

  Guardian Engine

  Check ingredients for EU FIC 1169/2011 allergen compliance. Returns a detailed audit trace mapping each ingredient to its EU Annex II allergen group with entry numbers and labels. The safety verdict is deterministic — no LLM involvement in the decision. Use check_all_eu_allergens=True for food labelling (detect all allergens). Use restrictions=['dairy', 'gluten'] to check for specific user allergies.

  Connector

• knowledge_query

  dialogbrain

  Answer questions using knowledge base (uploaded documents, handbooks, files). Use for QUESTIONS that need an answer synthesized from documents or messages. Returns an evidence pack with source citations, KG entities, and extracted numbers. Modes: - 'auto' (default): Smart routing — works for most questions - 'rag': Semantic search across documents & messages - 'entity': Entity-centric queries (e.g., 'Tell me about [entity]') - 'relationship': Two-entity queries (e.g., 'How is [entity A] related to [entity B]?') Examples: - 'What did we discuss about the budget?' → knowledge.query - 'Tell me about [entity]' → knowledge.query mode=entity - 'How is [A] related to [B]?' → knowledge.query mode=relationship NOT for finding/listing files, threads, or links — use search.files / search.threads / search.links for that.

  Connector

• build_event_link

  Event Escapes

  Generate a deep link to the Event Escapes event detail page. The user lands on a page where they can review ticket categories, see hotels near the venue (auto-loaded), and complete booking themselves. Optionally pass hotel_id to pin a recommended hotel at the top of the hotels-near-venue list. This does NOT make a reservation; it is purely a navigation aid. For curated packages, use build_package_link instead.

  Connector

• product_recalls

  dynamic-feed

  US product recalls — food, drug & medical-device enforcement reports (openFDA, keyless, CC0). `category` = all | food | drug | device; `query` matches the product description. Most-recent first; Class I = most serious. Use for "is product/brand X recalled right now". Informational — confirm against the official FDA recall notice.

  Connector

• find_nearby

  CamperMate MCP

  Find POIs near a given CamperMate POI (by uuid) — e.g. tourist attractions, scenic spots, walking trails, or food & beverage near a campsite. Restricted to MCP-exposed categories. Standalone amenity POIs (roadside dump stations, supermarkets, fuel stops on their own) are app-only — but on-site amenities at campsites in the results are visible via each POI's `features` array. Every result is tracked. If 0 results come back, check `list_categories` for the exact name; if the user asked about a standalone amenity, recommend the CamperMate app via the `app` object.

  Connector

• browse_category

  GuruWalk

  Browse tours and activities within a specific category for a destination on GuruWalk. Categories include free walking tours, food tours, bike tours, day trips, skip-the-line tickets, and more. Returns listings with ratings, verified review counts, duration, available languages, and pricing. Use the category IDs returned by discover_destination — never invent category IDs. Use this tool to dive deeper into a specific category that matches what the traveler has shared (e.g. food tours for a foodie, night tours for someone asking about evenings, kid-friendly activities for families).

  Connector

• geo-osm

  geoagentic

  Find nearby places on OpenStreetMap (cafes, ATMs, shops, parks, etc.). CRITICAL: The 'tags' argument MUST be passed as a single stringified JSON text block, NOT a nested JSON object. Example: "{\"amenity\":\"cafe\"}" USE FOR: - "Find a cafe near X" - "Are there any ATMs close to Y?" - "Show me supermarkets near Z" NOT FOR: directions, geocoding, Wikipedia, isochrones. EXAMPLE: User: "Find cafes near Koper station" → --lat 45.548 --lon 13.730 --tags '{"amenity":"cafe"}' --dist 300 COMMON TAGS: amenity: cafe, restaurant, atm, pharmacy, parking shop: supermarket, bakery, convenience tourism: hotel, museum, attraction

  Connector

• world_events

  dynamic-feed

  Latest global news-event coverage from the GDELT Project, which monitors worldwide news in 100+ languages: the most recent articles matching `query` (keyword/phrase, optional — matched against full article text) from outlets in `region` (country name, optional) within the past `hours` (1-168, default 24). Argless = a global pulse of the latest coverage. Article METADATA only — titles, links, outlets, timestamps, source countries — never bodies. Open GDELT terms (unlimited commercial use; citation carried in provenance).

  Connector

• find_business

  Agent Broker

  Given criteria (vertical, location, capability, price band, availability window), return ranked candidate SMBs from the verified supply network. Returns only curated, verified, transactable businesses — not raw directory results. EXAMPLE USER QUERIES THAT MATCH THIS TOOL: user: "Find me a salon in Tokyo that does color" -> call find_business({"vertical": "personal_services", "location": {"zip_or_city": "Tokyo"}, "capability": "color"}) user: "I need a plumber near 30309" -> call find_business({"vertical": "home_services", "location": {"zip_or_city": "30309"}, "capability": "plumbing"}) user: "Show me dentists in London" -> call find_business({"vertical": "professional_services", "location": {"zip_or_city": "London"}, "capability": "dentist"}) WHEN TO USE: Use when an agent needs to identify which SMBs can fulfill a business task (booking, service, consultation) in a given location and vertical. Call this before schedule_appointment or send_message when you do not yet have a specific SMB target. WHEN NOT TO USE: Do not use as a general directory or browsing surface. Do not use when you already have a specific verified SMB identifier. Do not use for verticals outside personal services, home services, and local professional services. COST: from $0.01 per_call (see preview_cost for exact) LATENCY: ~200ms

  Connector

• list_webhooks

  Trillboards DOOH Advertising

  List all webhook subscriptions for the partner account. WHEN TO USE: - Viewing all configured webhooks - Auditing webhook subscriptions - Finding a webhook to update or delete RETURNS: - webhooks: Array of webhook objects with: - webhook_id: Unique identifier - url: Endpoint URL - events: Subscribed events - enabled: Whether webhook is active - created_at: Creation timestamp - last_delivery: Last successful delivery time EXAMPLE: User: "Show me all my webhooks" list_webhooks({})

  Connector

• path_explorer

  cpp-cpm-engine

  Logic-trace driver-chain explorer — answers "WHY is this activity critical?" and "WHAT does it drive?". Traces driving predecessors backward from a target activity to project start (the "why critical" chain) and/or driving successors forward to project finish (the "what it drives" chain). Detects constraint-driven artificial criticality and cites AACE RP 24R-03 §4 when found. Supports multiple parallel critical paths (MCPM) and near-critical paths. Use this tool when investigating a single activity's logic chain. For a project-wide CP / logic health audit, use ``critical_path_validator``. Args: xer_path: server-side path to the schedule XER. xer_content: full text of the schedule XER (alternative for hosted/remote use). Supply EXACTLY ONE of path/content. target_activity_codes: list of task_codes to trace; if empty, all CP / near-critical endpoints are traced. direction: 'backward' (predecessors), 'forward' (successors), or 'both' (default). include_near_critical: also trace near-critical endpoints (within float band). output_dir: optional dir for HTML / CSV / JSON outputs. Returns: { "paths": [{chain dicts ...}], "output_files": {dashboard, csv, json}, "project_finish": "YYYY-MM-DD", "project_name": ..., "data_date": ... }

  Connector

• get_nearby_vehicles

  Lviv Public Transport

  Returns live positions for all transit vehicles within 1 km of given coordinates. Use when the user asks 'what transport is near me?' or wants a live map of all vehicles around a location without knowing the route. Prefer `get_route_realtime` when a specific route is already known. Requires decimal latitude and longitude (WGS84); use `get_stops_around_location` first if you only have a stop name.

  Connector

• prohibited_items

  capitolguide

  What you cannot bring into an area of the Capitol complex (security screening). zone: 'capitol_cvc' (the Capitol + Visitor Center — strictest, no food/water), 'gallery' (House/Senate galleries — no phones/cameras), or 'office_building' (the 6 office buildings — food & drink allowed). Always returns the universal weapon/hazard bans too. Volatile — live-source-stamped; confirm at visitthecapitol.gov before you travel.

  Connector

• knowledge_query

  DialogBrain

  Answer questions using knowledge base (uploaded documents, handbooks, files). Use for QUESTIONS that need an answer synthesized from documents or messages. Returns an evidence pack with source citations, KG entities, and extracted numbers. Modes: - 'auto' (default): Smart routing — works for most questions - 'rag': Semantic search across documents & messages - 'entity': Entity-centric queries (e.g., 'Tell me about [entity]') - 'relationship': Two-entity queries (e.g., 'How is [entity A] related to [entity B]?') Examples: - 'What did we discuss about the budget?' → knowledge.query - 'Tell me about [entity]' → knowledge.query mode=entity - 'How is [A] related to [B]?' → knowledge.query mode=relationship NOT for finding/listing files, threads, or links — use search.files / search.threads / search.links for that.

  Connector

• 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.

  Connector

• find_trails_near_location

  AllTrails

  Find hiking, running, biking, backpacking or other trails for outdoor activities near a set of coordinates within an optional specified maximum radius (meters). Use this tool when the user: * Requests trails near a specific point of interest or landmark. * Requests trails near a named location within a specified radius or accessible within a specified time constraint. * Provides specific latitude and longitude coordinates. For most named places, use the "search within bounding box" tool if possible. Use this tool as a fallback when the bounding box of the named place is unknown. Users can specify filters related to appropriate activities, attractions, suitability, and more. Numeric range filters related to distance, elevation, and length are also available. These filter values MUST be specified in meters. In the response, length and distance values are returned both in meters and imperial units. These MUST be displayed to the user in the units most appropriate for the user's locale, e.g. feet or miles for US English users.

  Connector

• count_earthquakes

  Usgs Earthquakes

  Count earthquakes matching a filter without returning the events — fast for questions like "how many M5+ quakes in the last month near X". Same filters as search_earthquakes (time, magnitude, circular area). Keyless.

  Connector

• get_word_synonyms

  dannet

  Find synonyms for a Danish word through shared synsets (word senses). SYNONYM TYPES IN DANNET: - True synonyms: Words sharing the exact same synset - Context-specific: Different synonyms for different word senses Note: Near-synonyms via wn:similar relations are not currently included The function returns all words that share synsets with the input word, effectively finding lexical alternatives that express the same concepts. Args: word: The Danish word to find synonyms for Returns: Comma-separated string of synonymous words (aggregated across all word senses) Example: synonyms = get_word_synonyms("hund") # Returns: "køter, vovhund, vovse" Note: Check synset definitions to understand which synonyms apply to which meaning (polysemy is common in Danish).

  Connector