OpenDealer MCP Server

{
  "id": "aix_2f699b1af4",
  "name": "OpenDealer MCP Server",
  "operator": "(unclaimed - source: registry-official · publisher: app.opendealer)",
  "description": "Automotive inventory search for AI assistants: vehicles, dealers, deals, and market data.",
  "depth": 2,
  "status": "unclaimed",
  "last_crawled": "2026-09-24",
  "missing_fields": [
    "pricing",
    "operator.identity"
  ],
  "skills": [
    "data-enrichment",
    "inventory-check",
    "market-data"
  ],
  "protocols": {
    "mcp": "https://mcp.opendealer.app/rpc",
    "a2a": null
  },
  "pricing": null,
  "regions": [
    "global"
  ],
  "languages": [
    "en"
  ],
  "reputation": {
    "tasks_completed": null,
    "dispute_rate": null,
    "p95_latency_ms": 3271,
    "uptime_30d": 1,
    "onchain_volume_30d_usd": null
  },
  "aix_score": 41,
  "verification": {
    "identity": "none",
    "health": "probe/24h",
    "pricing": "unknown",
    "last_check": "2026-09-24T22:00:44.380Z"
  },
  "pricing_model": "unknown",
  "links": [
    {
      "label": "homepage",
      "url": "https://opendealer.pro/"
    }
  ],
  "profile": {
    "mcp_server": "OpenDealer MCP Server",
    "mcp_version": "2.2.2",
    "tool_count": 27,
    "tools": [
      {
        "name": "search_vehicles",
        "description": "Search for vehicles across dealerships (Meilisearch-backed NL + structured filters).\n\nPreferred tool order for assistants:\n1. list_facets or list_research_makes/list_research_models to discover valid values\n2. filter_vehicles (map shopper intent onto labeled hard filters)\n3. get_vehicle / get_deal_score / research_model for depth\n\nWhen the ask implies analysis (good deal?, safety, budget, timing, dealer plan), continue with a shopping playbook from initialize instructions or resource opendealer://assistant/shopping-playbooks — do not stop at raw search results.\n\nLocation modes (choose ONE): zi"
      },
      {
        "name": "filter_vehicles",
        "description": "Preferred structured inventory lookup when make/model/year/color/location are known.\n\nUses exact hard filters (keyword mode, no embeddings) via the Runtime /v1/llm/filter path. Resolve exact make/model names with list_research_makes and list_research_models first. Map shopper prose onto labeled keys (make, model, body, price_max, location); do not dump the sentence into search_vehicles.\n\nOften the first step in shopping playbooks (budget_coach, safety_first, price_drop_sniper, dealer_crawl). After results, chain get_deal_score / get_vehicle_history / check_recalls / compare_vehicles when the u"
      },
      {
        "name": "list_facets",
        "description": "Discover available filter values and counts (makes, body types, fuel types, price/year ranges) for the live inventory.\n\nCall this before filter_vehicles when you need valid dimension values. Optional make/near/radius scopes the facet counts."
      },
      {
        "name": "list_research_makes",
        "description": "Browse the research catalog of vehicle makes (with model and inventory counts). Use to resolve exact make names/slugs before filter_vehicles or research_model."
      },
      {
        "name": "list_research_models",
        "description": "List models for a make from the research catalog (MSRP/body summaries). Use before filter_vehicles or research_model when the model name is uncertain."
      },
      {
        "name": "get_vehicle",
        "description": "Get complete details for a specific vehicle by VIN.\n\nReturns comprehensive Schema.org Vehicle data including:\n• Full specifications (engine, transmission, drivetrain)\n• High-resolution images\n• Current pricing and availability\n• NHTSA NCAP safety rating summary (when available)\n• NHTSA open recall summary (YMM-granular, when available)\n• Dealer contact information\n\nStarting point for the vehicle_dossier playbook. For buy/no-buy questions, continue with get_deal_score → get_vehicle_history → check_recalls → get_similar_vehicles.\n\nCRITICAL: CITE: Each vehicle's cite object is `vin` + `url` (cano"
      },
      {
        "name": "check_recalls",
        "description": "Get NHTSA open safety recalls for a vehicle by VIN.\n\nReturns recall campaigns resolved at the year/make/model level (YMM-granular). A recall listed for the model year may not apply to every VIN — the response includes NHTSA's disclaimer and campaign details (component, summary, remedy status, Park It / Park Outside advisories).\n\nUse this when a shopper asks about recalls, safety campaigns, or whether a specific model has open NHTSA notices. Required step in vehicle_dossier and safety_first playbooks; always include the YMM-granularity disclaimer."
      },
      {
        "name": "get_dealer",
        "description": "Get comprehensive information about a specific dealership.\n\nReturns Google-enriched dealer knowledge optimized for assistants:\n• Name, address, phone, website\n• Google rating, review count, hours, business status\n• Inventory count and OpenDealer profile links\n• Contact points for sales / customer service\n\nUse this when a shopper asks \"tell me about X dealership\" or needs hours/ratings for a known dealer. Prefer a slug from dealers_near or search results.\n\nCRITICAL: Only use URL fields from the response (website, urls.*). NEVER invent or construct URLs."
      },
      {
        "name": "get_safety_rating",
        "description": "Get NHTSA 5-Star Safety Ratings for a year/make/model (no VIN required).\n\nAnswers questions like \"is a 2023 RAV4 safe for my family\" with:\n• Overall and crash-test star ratings (when published)\n• Rollover rating / possibility\n• NHTSA-evaluated ADAS availability (ESC, FCW, LDW)\n\nRatings are model-year granular from the NHTSA NCAP cache. If no confident rating exists, the tool reports that honestly rather than guessing. For VIN-specific listing details use get_vehicle; for open recalls use check_recalls.\n\nCRITICAL: Only use the 'sourceUrl' field from the response for NHTSA links. NEVER invent UR"
      },
      {
        "name": "get_vehicle_history",
        "description": "Get OpenDealer listing history for a VIN: price changes, days on lot, and status.\n\nAnswers \"has this VIN dropped in price\" and days-on-lot narratives from retained snapshots (including vehicles that left a dealer feed). Returns:\n• Chronological price history with per-snapshot changes\n• Days on market / lot signals and badges (price_drop, long_on_lot)\n• Active vs no-longer-listed status when known\n\nDoes not invent a deal score for sold vehicles — use get_deal_score for live market scoring. Essential for price_drop_sniper and vehicle_dossier playbooks when shoppers ask about reductions or negoti"
      },
      {
        "name": "dealers_near",
        "description": "Find dealerships near a location.\n\nLocation modes (choose ONE):\n• zip + radius (miles)\n• lat + lng + radius\n• city + state + radius\n• county + state + radius\n\nReturns dealer information including:\n• Name, address, phone, website\n• Distance from search location\n• Current inventory count\n• Business hours (when available)"
      },
      {
        "name": "dealer_inventory",
        "description": "Browse the complete inventory of a specific dealership.\n\nIMPORTANT: Use the exact dealer slug from a previous dealers_near or search_vehicles response. Do NOT guess dealer IDs.\n\nUseful when a user wants to see what a particular dealer has in stock.\nSupports all vehicle filters (make, model, price, etc.).\n\nCRITICAL: CITE: Each vehicle's cite object is `vin` + `url` (canonical opendealer.shop VDP). Cite only `url` to shoppers. Never invent VDP URLs. Never cite `detailsUrl` (dealer/LotLinx). Never send shoppers to `/llm/*` HTML or `/v1/llm/*` as the human listing URL."
      },
      {
        "name": "compare_vehicles",
        "description": "Compare 2-5 vehicles side by side.\n\nReturns a structured comparison including specs, price context, and per-vehicle cite fields (vin + shop url).\n\nCRITICAL: CITE: Each vehicle's cite object is `vin` + `url` (canonical opendealer.shop VDP). Cite only `url` to shoppers. Never invent VDP URLs. Never cite `detailsUrl` (dealer/LotLinx). Never send shoppers to `/llm/*` HTML or `/v1/llm/*` as the human listing URL."
      },
      {
        "name": "get_deal_score",
        "description": "Get AI-powered deal scoring and market insights for a vehicle.\n\nReturns comprehensive analysis including:\n• Deal score (1-100) with rating (Great, Good, Fair, Poor)\n• Price comparison vs market average\n• Days on lot analysis\n• Price history and trends\n• Similar vehicles in the market\n\nCore step in vehicle_dossier, budget_coach, price_drop_sniper, and dealer_crawl playbooks. Pair with get_vehicle_history and check_recalls for buy/no-buy answers."
      },
      {
        "name": "get_market_overview",
        "description": "Get high-level automotive market statistics.\n\nReturns aggregated market data including:\n• Total vehicles and dealers in inventory\n• Average pricing by segment\n• Top makes by volume\n• Market velocity indicators\n• New vs Used breakdown"
      },
      {
        "name": "get_market_segment",
        "description": "Get detailed pricing and market data for a specific vehicle segment.\n\nUseful for understanding fair market value for a make/model/year combination.\nReturns pricing statistics including:\n• Average, median, min, max prices\n• Price percentiles (10th, 25th, 75th, 90th)\n• Average mileage and days on lot\n• Certified vs non-certified pricing difference"
      },
      {
        "name": "list_market_segments",
        "description": "Browse market segments with pricing statistics (modelcode, median price, sample size). Use to discover modelcodes for get_market_segment / get_market_trends."
      },
      {
        "name": "get_market_trends",
        "description": "Price trends over time for a market segment (modelcode). Returns timeline of median/avg prices and days-on-lot."
      },
      {
        "name": "get_market_velocity",
        "description": "How quickly vehicles sell by segment (fastest/slowest days on lot). Optional make/type filters."
      },
      {
        "name": "compare_market",
        "description": "Compare pricing across market segments. Provide modelcodes[] or make (optionally with model)."
      },
      {
        "name": "get_suggested_rates",
        "description": "National average suggested auto loan APRs (not a credit offer). Optional filters: condition (new/used), term_months (36–84), credit_tier."
      },
      {
        "name": "research_model",
        "description": "Get the full research payload for a vehicle model (not a specific listing).\n\nReturns manufacturer reference data joined with live market data:\n• All trims with MSRPs, engine/body specs, and EPA fuel economy\n• NHTSA 5-Star safety ratings and open recall count\n• Live inventory count and price range on OpenDealer\n\nUse this when a shopper asks \"tell me about the Honda Civic\", \"what trims does the RAV4 come in\", or \"how much is a 2025 F-150\". For a specific listed vehicle, use get_vehicle with a VIN instead.\n\nCRITICAL: Only use the 'url' field from the response for links. NEVER invent or construct "
      },
      {
        "name": "compare_models",
        "description": "Compare 2-4 vehicle models side by side (model-level, not specific listings).\n\nProvide composite make-model slugs like \"honda-civic\" or \"toyota-corolla\". Returns:\n• Winner-by-dimension deltas: price, fuel economy, horsepower, seating, towing, NHTSA safety, live median listing price\n• Full research payload for each model (trims, MSRPs, specs)\n\nUse this for \"Civic vs Corolla\" style questions. To compare specific listed vehicles by VIN, use compare_vehicles instead.\n\nCRITICAL: Only use the 'url' field from the response for links. NEVER invent or construct URLs."
      },
      {
        "name": "get_vehicle_rankings",
        "description": "Get data-driven vehicle rankings (e.g., best SUVs, most fuel-efficient cars).\n\nCall without arguments to list all ranking categories. Pass a category slug (e.g., \"best-suvs\") for the full scored ranking.\n\nRankings are computed from public data with a published methodology: NHTSA safety ratings, EPA fuel economy, manufacturer pricing, and live market availability. There is no paid placement; each entry includes its transparent score breakdown.\n\nCRITICAL: Only use the 'url' field from the response for links. NEVER invent or construct URLs."
      },
      {
        "name": "get_similar_vehicles",
        "description": "Find similar on-lot vehicles for a VIN (\"you may also like\"). Same make/model keyword comps as the shop VDP rail (not semantic embeddings).\n\nCRITICAL: CITE: Each vehicle's cite object is `vin` + `url` (canonical opendealer.shop VDP). Cite only `url` to shoppers. Never invent VDP URLs. Never cite `detailsUrl` (dealer/LotLinx). Never send shoppers to `/llm/*` HTML or `/v1/llm/*` as the human listing URL."
      }
    ],
    "profiled_at": "2026-09-24T22:00:44.380Z"
  },
  "unreachable": false
}