How to integrate Postal Data API MCP with Pydantic AI

This guide walks you through connecting Postal Data API to Pydantic AI using the Composio tool router. By the end, you'll have a working Postal Data API agent that can look up postal codes, validate your postal codes, search by city, and get location metadata through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Postal Data API account through Composio's Postal Data API MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Postal Data API is a global postal code validation and lookup service. Use it to verify locations, coordinates, and regional data across 240+ countries.

6 Tools

Introduction

This guide walks you through connecting Postal Data API to Pydantic AI using the Composio tool router. By the end, you'll have a working Postal Data API agent that can look up postal codes, validate your postal codes, search by city, and get location metadata through natural language commands.

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

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

Also integrate Postal Data API 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 Postal Data API
  • 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 Postal Data API 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 Postal Data API MCP server, and what's possible with it?

The Postal Data API MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Postal Data API account. It provides structured and secure access to global postal code and location data, so your agent can validate postal codes, look up locations and coordinates, search postal codes by city, retrieve regional metadata, and check service information on your behalf.

  • Postal code validation: Have your agent check whether a postal code exists without treating an invalid code as an execution error.
  • Bulk postal code checks: Instruct your agent to validate up to 1,000 postal codes at once, including codes from different countries.
  • Location and coordinate lookup: Let the agent find the city, region, and coordinates associated with a postal code.
  • City-based postal code search: Direct your agent to find postal codes for a city and optional region, including close matches.
  • Regional details and service status: Have your agent retrieve available timezone, county, elevation, and administrative details for a postal code, or check coverage, guidance, balance, and rate-limit status.

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 Postal Data API
  • 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 Postal Data API
  • MCPServerStreamableHTTP connects to the Postal Data API 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 Postal Data API
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["postal_data_api"],
    )
    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 Postal Data API 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
postal_data_api_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[postal_data_api_mcp],
    instructions=(
        "You are a Postal Data API assistant. Use Postal Data API tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Postal Data API endpoint
  • The agent uses GPT-5 to interpret user commands and perform Postal Data API 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 Postal Data API.\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
  • Postal Data API 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 Postal Data API 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 Postal Data API
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["postal_data_api"],
    )
    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
    postal_data_api_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[postal_data_api_mcp],
        instructions=(
            "You are a Postal Data API assistant. Use Postal Data API 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 Postal Data API.\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 Postal Data API through Composio's Tool Router. With this setup, your agent can perform real Postal Data API 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 + Postal Data API 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 Postal Data API action and event your agent gets out of the box.

Get API Information

Return Postal Data API version, coverage, usage guidance, current balance, and configured rate-limit status when returned, for connectivity or service discovery.

Get Postal Code Metadata

Return all available country-specific metadata for a postal code, such as coordinates, timezone, county, elevation, and administrative levels.

Look Up Postal Code

Look up the city, region, and coordinates for a postal code.

Search Postal Codes by City

Return all postal codes matching a city and optional region, including fuzzy-match details.

Validate Postal Code

Check whether one postal code exists without treating a nonexistent code as an execution error.

Validate Postal Codes in Bulk

Validate 1 to 1,000 postal codes synchronously, including mixed-country batches.

FRAMEWORKS

How to build Postal Data API MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Postal Data API MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Postal Data API MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Postal Data API MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Postal Data API MCP with Claude Cowork

Codex logo

Codex

Use Postal Data API MCP with Codex

OpenClaw logo

OpenClaw

Use Postal Data API MCP with OpenClaw

Hermes logo

Hermes

Use Postal Data API MCP with Hermes

CLI logo

CLI

Use Postal Data API MCP with CLI

Google ADK logo

Google ADK

Use Postal Data API MCP with Google ADK

LangChain logo

LangChain

Use Postal Data API MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Postal Data API MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Postal Data API MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Postal Data API MCP with LlamaIndex

CrewAI logo

CrewAI

Use Postal Data API MCP with CrewAI

FAQ

Frequently asked questions

With a standalone Postal Data API MCP server, the agents and LLMs can only access a fixed set of Postal Data API tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Postal Data API 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 Postal Data API tools.

Yes, absolutely. You can configure which Postal Data API 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 Postal Data API data and credentials are handled as safely as possible.

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