How to integrate Postal Data API MCP with CrewAI

This guide walks you through connecting Postal Data API to CrewAI 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 CrewAI 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 CrewAI 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 CrewAI 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 AILlamaIndex

TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Postal Data API connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Postal Data API
  • Build a conversational loop where your agent can execute Postal Data API operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

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 step08 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Postal Data API connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python
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 crewai crewai-tools[mcp] python-dotenv
What's happening:
  • composio connects your agent to Postal Data API via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] includes MCP helpers
  • python-dotenv loads environment variables from .env
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_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model
5

Import dependencies

python
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Postal Data API MCP URL
6

Create a Composio Tool Router session for Postal Data API

python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["postal_data_api"])

url = session.mcp.url
What's happening:
  • You create a Postal Data API only session through Composio
  • Composio returns an MCP HTTP URL that exposes Postal Data API tools
7

Initialize the MCP Server

python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
What's Happening:
  • Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
  • MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
  • Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
  • Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
  • Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.
8

Create a CLI Chatloop and define the Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")

conversation_context = ""

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[agent], tasks=[task], verbose=False)
    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's Happening:
  • Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
  • Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
  • Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
  • Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
  • Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
  • Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.

Complete Code

Here's the complete code to get you started with Postal Data API and CrewAI:

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["postal_data_api"],
)
url = session.mcp.url

# Configure LLM
llm = LLM(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY"),
)

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\n")

    conversation_context = ""

    while True:
        user_input = input("You: ").strip()

        if user_input.lower() in ["exit", "quit", "bye"]:
            print("\nGoodbye!")
            break

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

Conclusion

You now have a CrewAI agent connected to Postal Data API through Composio's Tool Router. The agent can perform Postal Data API operations through natural language commands.

Next steps:

  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations
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

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. CrewAI 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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