# Carrier Vetting MCP — FMCSA Risk Verdicts (`irreplaceable_chevrotain/carrier-vetting-mcp`) Actor Carrier risk verdicts for AI agents — "should I trust this trucking carrier?" answered from official FMCSA data: authority, insurance, inspections, OOS rates, crash history, composed into a LOW/MEDIUM/HIGH verdict with flags. Pay per check, no subscription. - **URL**: https://apify.com/irreplaceable\_chevrotain/carrier-vetting-mcp.md - **Developed by:** [Gad](https://apify.com/irreplaceable_chevrotain) (community) - **Categories:** MCP servers, AI, Agents - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $150.00 / 1,000 full carrier vetting verdicts 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 ## Carrier Vetting MCP — FMCSA Risk Verdicts **Vet any US motor carrier before you tender a load: authority history, insurance lapses, safety record, and chameleon-carrier detection — from official FMCSA data, in one MCP call.** Double-brokering and carrier-identity fraud cost the freight industry billions a year, and the incumbents that screen for it (Highway, RMIS, Carrier411) are seat-licensed platforms priced for enterprises — $1.25+ per raw lookup, $500+/month commitments. The underlying data is free and public. This hosted [MCP (Model Context Protocol)](https://modelcontextprotocol.io) server sells the *judgment*, per call: connect it to Claude, ChatGPT, Cursor, n8n, or any MCP-capable agent and ask: - *"Who is USDOT 264184 and are they active?"* - *"Has this carrier's authority ever been revoked?"* - *"Is their insurance on file, and has it been cancelled recently?"* - *"Should I onboard this carrier?"* → one `vet_carrier` call returns a scored risk verdict with evidence. ### Tools | Tool | What it answers | Event charged | |---|---|---| | `lookup_carrier` | USDOT → legal name, DBA, status, address, officers, fleet, docket | `carrier-lookup` | | `authority_history` | Every grant / revocation / reinstatement with dates and reasons | `history-check` | | `insurance_status` | Public liability/cargo filings + full cancellation history | `history-check` | | `safety_snapshot` | 24-month inspections, out-of-service rates vs national averages, crashes, federal safety rating | `safety-check` | | `vet_carrier` | **The flagship:** all of the above + chameleon cross-reference → LOW / MODERATE / HIGH / CRITICAL verdict with evidence-backed flags | `carrier-vetted` | The chameleon check cross-references the carrier's address, phone, and officers against all 4.4M FMCSA registrations, surfaces FMCSA's own prior-revocation links, and distinguishes corporate families (Schneider's nine registrations at one Green Bay address are not fraud) from reincarnation patterns (a 6-month-old carrier sharing a phone number with two revoked ones is). Outputs are compact structured JSON built for agents — every flag carries a severity, a plain-English explanation, and the evidence behind it. ### 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": { "carrier-vetting": { "url": "https://.apify.actor/mcp", "headers": { "Authorization": "Bearer " } } } } ```` ### Batch mode Running the Actor directly (non-standby) vets a list of USDOT numbers from the input into the dataset — useful for screening an existing carrier roster. Each carrier charges one `carrier-vetted` event. ### Who uses this Freight brokers and dispatchers (pre-onboarding checks, tender-time re-checks), factoring companies (carrier risk before buying invoices), shippers running direct-carrier programs, insurtech underwriting flows, and AI agents that book freight. ### Data & disclaimer All data comes from official FMCSA (US Department of Transportation) public sources: the SAFER Company Snapshot, the Company Census File, and the Motus-era Licensing & Insurance datasets on data.transportation.gov. This Actor is not affiliated with or endorsed by FMCSA. **This is a pre-screen, not identity verification.** Public data can lag reality by days-to-weeks; a LOW verdict is not a guarantee, and a HIGH verdict deserves human review, not automatic blacklisting. Always verify a current certificate of insurance directly with the insurer before tendering. Crash counts represent involvement in reportable crashes without any determination of responsibility (per FMCSA policy). # Actor input Schema ## `usdotNumbers` (type: `array`): USDOT numbers to vet in batch mode (direct Actor runs). The primary product is the MCP server endpoint — see README. ## `includeChameleonCheck` (type: `boolean`): Cross-reference address, phone, and officers against the full FMCSA census for reincarnation signals (slower, more thorough). ## Actor input object example ```json { "usdotNumbers": [ "264184" ], "includeChameleonCheck": true } ``` # 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 = { "usdotNumbers": [ "264184" ] }; // Run the Actor and wait for it to finish const run = await client.actor("irreplaceable_chevrotain/carrier-vetting-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 = { "usdotNumbers": ["264184"] } # Run the Actor and wait for it to finish run = client.actor("irreplaceable_chevrotain/carrier-vetting-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 '{ "usdotNumbers": [ "264184" ] }' | apify call irreplaceable_chevrotain/carrier-vetting-mcp --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=irreplaceable_chevrotain/carrier-vetting-mcp", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Carrier Vetting MCP — FMCSA Risk Verdicts", "description": "Carrier risk verdicts for AI agents — \"should I trust this trucking carrier?\" answered from official FMCSA data: authority, insurance, inspections, OOS rates, crash history, composed into a LOW/MEDIUM/HIGH verdict with flags. Pay per check, no subscription.", "version": "0.1", "x-build-id": "g2n40PTdUW8lI0kuo" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/irreplaceable_chevrotain~carrier-vetting-mcp/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-irreplaceable_chevrotain-carrier-vetting-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/irreplaceable_chevrotain~carrier-vetting-mcp/runs": { "post": { "operationId": "runs-sync-irreplaceable_chevrotain-carrier-vetting-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/irreplaceable_chevrotain~carrier-vetting-mcp/run-sync": { "post": { "operationId": "run-sync-irreplaceable_chevrotain-carrier-vetting-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "usdotNumbers": { "title": "USDOT numbers", "type": "array", "description": "USDOT numbers to vet in batch mode (direct Actor runs). The primary product is the MCP server endpoint — see README.", "items": { "type": "string" } }, "includeChameleonCheck": { "title": "Include chameleon/reincarnation cross-reference", "type": "boolean", "description": "Cross-reference address, phone, and officers against the full FMCSA census for reincarnation signals (slower, more thorough).", "default": true } } }, "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 } } } } } } } } } } ```