How to integrate CarsXE MCP with Pydantic AI

This guide walks you through connecting CarsXE to Pydantic AI using the Composio tool router. By the end, you'll have a working CarsXE agent that can decode vin and summarize vehicle specs, check recalls for a used car, estimate market value from license plate through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a CarsXE account through Composio's CarsXE MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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CarsXE is a vehicle data API platform for VIN specs, recalls, license plate decoding, market values, history, images, and automotive lookups. Use it to turn raw vehicle identifiers into clear, useful car data fast.

12 Tools

Introduction

This guide walks you through connecting CarsXE to Pydantic AI using the Composio tool router. By the end, you'll have a working CarsXE agent that can decode vin and summarize vehicle specs, check recalls for a used car, estimate market value from license plate through natural language commands.

This guide will help you understand how to give your Pydantic AI agent real control over a CarsXE account through Composio's CarsXE MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate CarsXE with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for CarsXE
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your CarsXE workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

What is the CarsXE MCP server, and what's possible with it?

The CarsXE MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your CarsXE account. It provides structured and secure access to vehicle specifications, records, valuations, images, and diagnostic data, so your agent can decode vehicles, check recalls and history, estimate market values, diagnose OBD codes, and recognize license plates on your behalf.

  • Vehicle identification and specifications: Have your agent decode a VIN or license plate, or look up detailed vehicle and trim information by year, make, and model.
  • Recall and safety checks: Instruct your agent to find safety recalls for a VIN or vehicle model, or submit and review recall checks for many VINs.
  • History, lien, and theft research: Let the agent retrieve title, salvage, insurance, lien, theft, VIN change, and historical title records for a vehicle.
  • Market values and diagnostics: Direct your agent to estimate wholesale, retail, and trade-in values or translate an OBD-II trouble code into a readable diagnosis.
  • Vehicle images and plate recognition: Have your agent find vehicle photos by make and model or analyze a public image for license plate candidates and detected vehicle details.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account with an active API key
  • Basic familiarity with Python and async programming
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

bash
pip install composio pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like CarsXE
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs
5

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to CarsXE
  • MCPServerStreamableHTTP connects to the CarsXE MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for CarsXE
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["carsxe"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
What's happening:
  • We're creating a Tool Router session that gives your agent access to CarsXE tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
carsxe_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[carsxe_mcp],
    instructions=(
        "You are a CarsXE assistant. Use CarsXE tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the CarsXE endpoint
  • The agent uses GPT-5 to interpret user commands and perform CarsXE operations
  • The instructions field defines the agent's role and behavior
8

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with CarsXE.\n")

while True:
    user_input = input("You: ").strip()
    if user_input.lower() in {"exit", "quit", "bye"}:
        print("\nGoodbye!")
        break
    if not user_input:
        continue

    print("\nAgent is thinking...\n", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • CarsXE API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

Here's the complete code to get you started with CarsXE and Pydantic AI:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for CarsXE
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["carsxe"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    carsxe_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[carsxe_mcp],
        instructions=(
            "You are a CarsXE assistant. Use CarsXE tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with CarsXE.\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "bye"}:
            print("\nGoodbye!")
            break
        if not user_input:
            continue

        print("\nAgent is thinking...\n", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've built a Pydantic AI agent that can interact with CarsXE through Composio's Tool Router. With this setup, your agent can perform real CarsXE actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + CarsXE for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
TOOLS

Supported Tools

Every CarsXE action and event your agent gets out of the box.

Check Lien and Theft Records

Retrieve reportable US lien and theft events for a VIN.

Decode License Plate

Look up vehicle identity from a license plate using CarsXE's current global v2 decoder.

Decode OBD Code

Translate an OBD-II diagnostic trouble code into a readable diagnosis.

Get Vehicle Market Value

Estimate wholesale, retail, and trade-in values for a VIN using CarsXE's current v2 valuation, optionally adjusted for state, mileage, and condition.

Get Recall Batch

Make exactly one read request for a CarsXE recall batch.

Get Vehicle History

Retrieve title, brand, junk/salvage, insurance, VIN-change, and historical title records for a VIN.

Get Vehicle Images

Find up to 10 vehicle photos by make and model, with optional year, trim, angle, image type, size, color, quality, transparency, and license filters.

Get Vehicle Recalls

Find safety recall campaigns either for one VIN or for a year, make, and model.

Get Vehicle Specifications

Decode a 17-character VIN into vehicle identity, specifications, equipment, colors, and warranty data.

Get Year Make Model Data

Look up detailed vehicle and trim information by year, make, and model without a VIN.

Recognize License Plate

Analyze a publicly accessible vehicle image and return license-plate candidates, regions, confidence, bounding boxes, and detected vehicle details.

Submit Recall Batch

Create one asynchronous CarsXE recall-check batch for 1 to 10,000 VIN entries.

FRAMEWORKS

How to build CarsXE MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use CarsXE MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use CarsXE MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use CarsXE MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use CarsXE MCP with Claude Cowork

Codex logo

Codex

Use CarsXE MCP with Codex

OpenClaw logo

OpenClaw

Use CarsXE MCP with OpenClaw

Hermes logo

Hermes

Use CarsXE MCP with Hermes

CLI logo

CLI

Use CarsXE MCP with CLI

Google ADK logo

Google ADK

Use CarsXE MCP with Google ADK

LangChain logo

LangChain

Use CarsXE MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use CarsXE MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use CarsXE MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use CarsXE MCP with LlamaIndex

CrewAI logo

CrewAI

Use CarsXE MCP with CrewAI

FAQ

Frequently asked questions

With a standalone CarsXE MCP server, the agents and LLMs can only access a fixed set of CarsXE tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from CarsXE and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. Pydantic AI fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right CarsXE tools.

Yes, absolutely. You can configure which CarsXE scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your CarsXE data and credentials are handled as safely as possible.

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