OpenDealer MCP Server

Forgiving vehicle search (Meilisearch): natural-language q, typo-tolerant make/model/color, optional structured filters. Use when the shopper query is fuzzy or exploratory. Use filter_vehicles instead when make/model/year/body/price/location are known — it applies exact hard filters via /v1/llm/filter and returns trustworthy totals. Discovery order: list_facets / list_research_makes → filter_veh

Preferred structured inventory lookup when make/model/year/color/location are known. Exact hard filters only (keyword mode, no embeddings) via GET /v1/llm/filter. Totals match the filters you pass; there is no forgiving ranking boost. The Shop grid also requires a photo, so its count can be lower. Resolve make/model with list_research_makes / list_research_models first. Map shopper prose onto lab

Discover available filter values and counts (makes, body types, fuel types, price/year ranges) for the live inventory. Call this before filter_vehicles when you need valid dimension values. Optional make/near/radius scopes the facet counts.

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.

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.

Get complete details for a specific vehicle by listingId or VIN. When a VIN is listed at multiple dealer rooftops, a VIN-only lookup returns an envelope of every listing (type vehicle_listings) with no single-store price, seller, or url. Pass listingId to fetch one store. Returns comprehensive Schema.org Vehicle data including: • Full specifications (engine, transmission, drivetrain) • High-reso

Get NHTSA open safety recalls for a vehicle by VIN. Returns 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). Use this when a shopper asks about recalls, safety campaigns, or whet

Get comprehensive information about a specific dealership. Returns Google-enriched dealer knowledge optimized for assistants: • Name, address, phone, website • Google rating, review count, hours, business status • Inventory count and OpenDealer profile links • Contact points for sales / customer service Use this when a shopper asks "tell me about X dealership" or needs hours/ratings for a known

Get NHTSA 5-Star Safety Ratings for a year/make/model (no VIN required). Answers questions like "is a 2023 RAV4 safe for my family" with: • Overall and crash-test star ratings (when published) • Rollover rating / possibility • NHTSA-evaluated ADAS availability (ESC, FCW, LDW) Ratings are model-year granular from the NHTSA NCAP cache. If no confident rating exists, the tool reports that honestly

Get OpenDealer listing history for a VIN: price changes, days on lot, and status. Answers "has this VIN dropped in price" and days-on-lot narratives from retained snapshots (including vehicles that left a dealer feed). Returns: • Chronological price history with per-snapshot changes • Days on market / lot signals and badges (price_drop, long_on_lot) • Active vs no-longer-listed status when known

Find dealerships near a location. Location modes (choose ONE): • zip + radius (miles) • lat + lng + radius • city + state + radius • county + state + radius Returns dealer information including: • Name, address, phone, website • Slug (the public handle for get_dealer and dealer_inventory; the public list does not include internal dealer UUIDs) • Distance from search location • Current inventory

Browse the complete inventory of a specific dealership. IMPORTANT: Use the exact dealer slug from a previous dealers_near or search_vehicles response. Do NOT guess dealer IDs. Useful when a user wants to see what a particular dealer has in stock. Supports all vehicle filters (make, model, price, etc.). CRITICAL: CITE: Each vehicle's cite object is `vin` + `url` (canonical opendealer.shop VDP).

Compare 2-5 vehicles side by side. Returns a structured comparison including specs, price context, and per-vehicle cite fields (vin + shop url). CRITICAL: 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 l

Get AI-powered deal scoring and market insights for a vehicle. Returns comprehensive analysis including: • Deal score (1-100) with rating (Great, Good, Fair, Poor) • Price comparison vs market average • Days on lot analysis • Price history and trends • Similar vehicles in the market Core step in vehicle_dossier, budget_coach, price_drop_sniper, and dealer_crawl playbooks. Pair with get_vehicle_h

Get high-level automotive market statistics. Returns aggregated market data including: • Total vehicles and dealers in inventory • Average pricing by segment • Top makes by volume • Market velocity indicators • New vs Used breakdown

Get detailed pricing and market data for a specific vehicle segment. Useful for understanding fair market value for a make/model/year combination. Returns pricing statistics including: • Average, median, min, max prices • Price percentiles (10th, 25th, 75th, 90th) • Average mileage and days on lot • Certified vs non-certified pricing difference

Browse market segments with pricing statistics (modelcode, median price, sample size). Use to discover modelcodes for get_market_segment / get_market_trends.

Price trends over time for a market segment (modelcode). Returns timeline of median/avg prices and days-on-lot.

How quickly vehicles sell by segment (fastest/slowest days on lot). Optional make/type filters.

Compare pricing across market segments. Provide modelcodes[] or make (optionally with model).

National average suggested auto loan APRs (not a credit offer). Optional filters: condition (new/used), term_months (36–84), credit_tier.

Get the full research payload for a vehicle model (not a specific listing). Returns manufacturer reference data joined with live market data: • All trims with MSRPs, engine/body specs, and EPA fuel economy • NHTSA 5-Star safety ratings and open recall count • Live inventory count and price range on OpenDealer Use this when a shopper asks "tell me about the Honda Civic", "what trims does the RAV4

Compare 2-4 vehicle models side by side (model-level, not specific listings). Provide composite make-model slugs like "honda-civic" or "toyota-corolla". Returns: • Winner-by-dimension deltas: price, fuel economy, horsepower, seating, towing, NHTSA safety, live median listing price • Full research payload for each model (trims, MSRPs, specs) Use this for "Civic vs Corolla" style questions. To com

Get data-driven vehicle rankings (e.g., best SUVs, most fuel-efficient cars). Call without arguments to list all ranking categories. Pass a category slug (e.g., "suvs") for the full scored ranking. Rankings 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

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). CRITICAL: 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

App-only: record a vehicle selection from the results widget. Not for model use — hosts filter via _meta.ui.visibility.

App-only: paginate or refresh vehicle results using the same Runtime paths as filter_vehicles / search_vehicles (geo-correct). No widget remount — omit resourceUri. Not for model use.