# app.opendealer/mcp Automotive inventory search for AI assistants: vehicles, dealers, deals, and market data. - **Type:** MCP server - **Trust:** 60/100 (B), scored on the content rubric - **Verification:** community-indexed — nobody has claimed this listing - **Version:** 2.0.0 - **Author:** app.opendealer - **License:** Unknown - **Endpoints:** streamable-http https://mcp.opendealer.app/rpc - **Source:** https://opendealer.pro - **Endpoint health:** reachable (last checked 2026-09-08T16:51:17.265Z, 3 samples) — uptime is not a security property and is not part of the trust score - **Compatible clients:** claude-code, cursor, copilot, chatgpt, gemini (basis: transport) ## Trust 60/100 (B), scored on the content rubric - Publisher verified: no - Install scripts: nothing suspicious found - Prompt-injection scan: clean - Obfuscation scan: clean - Evidence age: 0 days ## Security scan - **Status:** clean - **Scanned:** 2026-09-08T16:51:17.265Z - **Version scanned:** live - **CVEs:** no coverage — this entry has no package coordinates to query OSV against, so "no known CVEs" is NOT asserted for it. ## Tools 27 declared. Observed from a live `tools/list` probe. - `search_vehicles` — Search for vehicles across dealerships (Meilisearch-backed NL + structured filters). Preferred tool order for assistants: 1. list_facets or list_research_makes/ - `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/l - `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 - `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, drivet - `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 - `get_dealer` — Get comprehensive information about a specific dealership. Returns Google-enriched dealer knowledge optimized for assistants: • Name, address, phone, website • - `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-te - `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 retain - `dealers_near` — Find dealerships near a location. Location modes (choose ONE): • zip + radius (miles) • lat + lng + radius • city + state + radius • county + state + radius Ret - `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 gu - `compare_vehicles` — 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: - `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, Po - `get_market_overview` — Get high-level automotive market statistics. Returns aggregated market data including: • Total vehicles and dealers in inventory • Average pricing by segment • - `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 prici - `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 M - `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 - `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., - `get_similar_vehicles` — 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 - `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 resource ## Install **Verdict: review** — Installable, but 2 things to check first: No CVE coverage: this entry has no npm/PyPI coordinates to query OSV against, so "no known vulnerabilities" is not a claim that can be made about it. **Cautions** (coverage gaps and advisories — never blocking) - No CVE coverage: this entry has no npm/PyPI coordinates to query OSV against, so "no known vulnerabilities" is not a claim that can be made about it. - No publisher has proved control of this listing; it is indexed, not vouched for. **Config** (claude-code): ```json "{\n \"mcpServers\": {\n \"mcp\": {\n \"type\": \"http\",\n \"url\": \"https://mcp.opendealer.app/rpc\"\n }\n }\n}" ``` ## Blast radius Contained to moderate — no credential declaration found, from the publisher, the upstream registry, or the README. Known so far: runs on someone else's infrastructure; read-only tool surface. - Floor 9, ceiling 27 (tier: unknown) - `unknown` means the floor and ceiling land in different bands — not measured enough to name one. It does not mean low. - This is impact, not likelihood. A high radius is not a defect: a filesystem server is supposed to write files. It is never part of the trust score. ## Machine-readable views of this entry - Signed JSON: https://forgeregistry.com/api/v1/packages/app.opendealer%2Fmcp - Install plan: https://forgeregistry.com/api/v1/packages/app.opendealer%2Fmcp/install-plan - Alternatives: https://forgeregistry.com/api/v1/alternatives/app.opendealer%2Fmcp - HTML page: https://forgeregistry.com/registry/app.opendealer%2Fmcp - MCP: POST https://forgeregistry.com/api/mcp → `forge_get_package` / `forge_install_plan` ## About this document Generated by Forge (https://forgeregistry.com) — a compact rendering of the same record served, signed, at the JSON URL above. Trust and scan facts are the registry's own measurements; anything Forge did not measure is named as unmeasured rather than omitted.