Automotive inventory search for AI assistants: vehicles, dealers, deals, and market data.
healthy
status
27
tools exposed
1322ms
connect latency
c6cb02539b58
schema fingerprint
Tools (27)
search_vehicles
Search for vehicles across dealerships (Meilisearch-backed NL + structured filters).
Preferred tool order for assistants:
1. list_facets or list_research_makes/list_research_models to discover valid values
2. filter_vehicles when make/model/year/price/location are known (exact hard filters)
3. sear
filter_vehicles
Preferred structured inventory lookup when make/model/year/color/location are known.
Uses 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. For prose or conceptual queries, us
list_facets
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.
list_research_makes
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_research_models
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_vehicle
Get complete details for a specific vehicle by VIN.
Returns comprehensive Schema.org Vehicle data including:
• Full specifications (engine, transmission, drivetrain)
• High-resolution images
• Current pricing and availability
• NHTSA NCAP safety rating summary (when available)
• NHTSA open recall s
check_recalls
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 I
get_dealer
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 se
get_safety_rating
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-yea
get_vehicle_history
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 marke
dealers_near
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
• Distance from search location
• Current inventory count
• Business ho
dealer_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, e
compare_vehicles
Compare 2-5 vehicles side by side.
Provide a list of VINs to compare. Returns a structured comparison including:
• Specifications comparison (engine, MPG, features)
• Price comparison with market context
• Pros and cons for each vehicle
• Recommendation based on value
get_deal_score
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 v
get_market_overview
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_market_segment
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
list_market_segments
Browse market segments with pricing statistics (modelcode, median price, sample size). Use to discover modelcodes for get_market_segment / get_market_trends.
get_market_trends
Price trends over time for a market segment (modelcode). Returns timeline of median/avg prices and days-on-lot.
get_market_velocity
How quickly vehicles sell by segment (fastest/slowest days on lot). Optional make/type filters.
compare_market
Compare pricing across market segments. Provide modelcodes[] or make (optionally with model).
get_suggested_rates
National average suggested auto loan APRs (not a credit offer). Optional filters: condition (new/used), term_months (36–84), credit_tier.
research_model
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
compare_models
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 p
get_vehicle_rankings
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., "best-suvs") for the full scored ranking.
Rankings are computed from public data with a published methodology: NHTSA safety ratings, EPA
get_similar_vehicles
Find similar on-lot vehicles for a VIN ("you may also like"). Uses semantic similarity when available, with make/model filter fallback.
CRITICAL: Use the 'url' or listing fields from each result. NEVER invent URLs.
ui_select_vehicle
App-only: record a vehicle selection from the results widget. Not for model use — hosts filter via _meta.ui.visibility.
ui_page_vehicle_results
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.
Endpoint
https://mcp.opendealer.app/rpc Category: AI & LLM · Last checked: 2026-07-30T12:47:48Z
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