# Vehicle Intelligence MCP (`irreplaceable_chevrotain/vehicle-intelligence-mcp`) Actor Vehicle safety intelligence for AI agents — VIN decoding, recall campaigns, owner complaints, and full safety profiles from official NHTSA data, one tool call each. MCP server over Streamable HTTP. Pay per lookup, no subscription. - **URL**: https://apify.com/irreplaceable\_chevrotain/vehicle-intelligence-mcp.md - **Developed by:** [Gad](https://apify.com/irreplaceable_chevrotain) (community) - **Categories:** AI, Agents, MCP servers - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $50.00 / 1,000 full vehicle safety profiles This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Vehicle Intelligence MCP **Give your AI agent complete knowledge of any US vehicle — VIN decoding, safety recalls, owner complaints, and crash-test ratings — from official NHTSA data, in one MCP server.** No API keys to manage, no scrapers to babysit. This is a hosted [MCP (Model Context Protocol)](https://modelcontextprotocol.io) server: connect it to Claude, ChatGPT, Cursor, or any MCP-capable agent and it can answer questions like: - *"What car is VIN 1HGCM82633A004352?"* - *"Does a 2019 Honda Accord have open recalls?"* - *"What do owners complain about most on the 2022 Insight?"* - *"Should I worry about buying this used car?"* → one `safety_profile` call ### Tools | Tool | What it answers | Event charged | |---|---|---| | `decode_vin` | VIN → year, make, model, trim, engine, transmission, plant | `vin-decoded` | | `check_recalls` | Official recall campaigns: component, consequence, remedy, urgency flags | `recall-check` | | `vehicle_complaints` | Owner complaint statistics: totals, crash/fire/injury tallies, worst components, recent excerpts | `complaint-check` | | `safety_profile` | Everything at once from a VIN or make/model/year: decode + crash ratings + recalls + complaints + key concerns | `safety-profile` | Outputs are compact, structured JSON designed for agents — empty fields stripped, dates normalized to ISO, summaries truncated so you don't pay tokens for noise. ### Connect Use the Actor's MCP endpoint (Standby mode) with any MCP client: ```` https://.apify.actor/mcp ```` Authenticate with your Apify token (`Authorization: Bearer `). Example Claude Code config: ```json { "mcpServers": { "vehicle-intelligence": { "url": "https://.apify.actor/mcp", "headers": { "Authorization": "Bearer " } } } } ```` ### Batch mode Running the Actor directly (non-standby) decodes a list of VINs from the input into the dataset — useful for cleaning inventory lists. Each decoded VIN charges one `vin-decoded` event (plus `recall-check` per VIN if enabled). ### Who uses this Dealer and fleet tooling (inventory enrichment, trade-in triage), automotive marketplaces (listing validation, safety badges), insurance and lending workflows (vehicle verification), and consumer agents (used-car research). ### Data & disclaimer All data comes from the [NHTSA](https://www.nhtsa.gov/) (US Department of Transportation) public APIs — vPIC, Recalls, Complaints, and Safety Ratings — and is US-government public data. This Actor is not affiliated with or endorsed by NHTSA. Information is provided as-is for research purposes; always verify open recalls with an authorized dealer using the full VIN before making purchase or repair decisions. # Actor input Schema ## `vins` (type: `array`): List of 17-character Vehicle Identification Numbers to decode in batch. Each decoded VIN is charged as one 'vin-decoded' event and pushed to the dataset. ## `includeRecalls` (type: `boolean`): If enabled, each decoded vehicle is also checked against NHTSA recall campaigns (charged as one 'recall-check' event per VIN). ## Actor input object example ```json { "vins": [ "1HGCM82633A004352" ], "includeRecalls": false } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "vins": [ "1HGCM82633A004352" ] }; // Run the Actor and wait for it to finish const run = await client.actor("irreplaceable_chevrotain/vehicle-intelligence-mcp").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "vins": ["1HGCM82633A004352"] } # Run the Actor and wait for it to finish run = client.actor("irreplaceable_chevrotain/vehicle-intelligence-mcp").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "vins": [ "1HGCM82633A004352" ] }' | apify call irreplaceable_chevrotain/vehicle-intelligence-mcp --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=irreplaceable_chevrotain/vehicle-intelligence-mcp", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Vehicle Intelligence MCP", "description": "Vehicle safety intelligence for AI agents — VIN decoding, recall campaigns, owner complaints, and full safety profiles from official NHTSA data, one tool call each. MCP server over Streamable HTTP. Pay per lookup, no subscription.", "version": "0.1", "x-build-id": "f2GpZvbgTg2UjR38T" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/irreplaceable_chevrotain~vehicle-intelligence-mcp/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-irreplaceable_chevrotain-vehicle-intelligence-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/irreplaceable_chevrotain~vehicle-intelligence-mcp/runs": { "post": { "operationId": "runs-sync-irreplaceable_chevrotain-vehicle-intelligence-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/irreplaceable_chevrotain~vehicle-intelligence-mcp/run-sync": { "post": { "operationId": "run-sync-irreplaceable_chevrotain-vehicle-intelligence-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "vins": { "title": "VINs to decode", "type": "array", "description": "List of 17-character Vehicle Identification Numbers to decode in batch. Each decoded VIN is charged as one 'vin-decoded' event and pushed to the dataset.", "items": { "type": "string" } }, "includeRecalls": { "title": "Include open recalls", "type": "boolean", "description": "If enabled, each decoded vehicle is also checked against NHTSA recall campaigns (charged as one 'recall-check' event per VIN).", "default": false } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```