How to integrate ITM Platform MCP with Pydantic AI

This guide walks you through connecting ITM Platform to Pydantic AI using the Composio tool router. By the end, you'll have a working ITM Platform agent that can create your projects, add tasks, search project data, update tasks, and aggregate portfolio data through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a ITM Platform account through Composio's ITM Platform MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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ITM Platform is a project and portfolio management platform for tasks, services, financials, risks, resources, and DataMart analytics. Use it to plan, track, and analyze work across portfolios with one connected source of truth.

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Introduction

This guide walks you through connecting ITM Platform to Pydantic AI using the Composio tool router. By the end, you'll have a working ITM Platform agent that can create your projects, add tasks, search project data, update tasks, and aggregate portfolio data through natural language commands.

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

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

Also integrate ITM Platform with

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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 ITM Platform
  • 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 ITM Platform 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 ITM Platform MCP server, and what's possible with it?

The ITM Platform MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your ITM Platform account. It provides structured and secure access to your projects, tasks, reference data, and DataMart analytics, so your agent can create projects and tasks, find and review work, update records, and analyze portfolio data on your behalf.

  • Project creation and planning: Have your agent create projects with schedules and the classifications used by your organization.
  • Task creation and updates: Let the agent create project tasks and update their descriptions, schedules, hierarchy, custom fields, and other supported details.
  • Project tracking and updates: Direct your agent to find projects, review their current details, and update selected project information.
  • Work search and reference data: Instruct your agent to search tasks across accessible projects and check your account's valid project or task statuses, priorities, and types.
  • Portfolio and service analytics: Have your agent search and aggregate read-only DataMart records to analyze project and service performance.

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

Aggregate DataMart Components

Run a bounded read-only DataMart aggregation over project and service records for portfolio analytics.

Create Project

Create an ITM Platform project with its schedule and optional account-specific classification IDs.

Create Task

Create a task in an ITM Platform project using account-defined type, priority, and status names.

Get Project

Return the full current details of one project by its ITM Platform project ID.

List Reference Data

List account-defined project or task statuses, priorities, or types needed to form valid project and task mutations.

Search DataMart Components

Search the read-only DataMart for project or service analytics records and return one offset-paginated page.

Search Projects

Search projects by account-specific filters and return one page of project summaries with a continuation cursor.

Search Tasks

Search tasks across accessible projects and return one page of task summaries with a continuation cursor.

Update Project

Update selected fields of an existing ITM Platform project and return the provider result.

Update Task

Update selected descriptive, scheduling, hierarchy, or custom fields on an existing ITM Platform project task.

FRAMEWORKS

How to build ITM Platform MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use ITM Platform MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use ITM Platform MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use ITM Platform MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use ITM Platform MCP with Claude Cowork

Codex logo

Codex

Use ITM Platform MCP with Codex

OpenClaw logo

OpenClaw

Use ITM Platform MCP with OpenClaw

Hermes logo

Hermes

Use ITM Platform MCP with Hermes

CLI logo

CLI

Use ITM Platform MCP with CLI

Google ADK logo

Google ADK

Use ITM Platform MCP with Google ADK

LangChain logo

LangChain

Use ITM Platform MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use ITM Platform MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use ITM Platform MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use ITM Platform MCP with LlamaIndex

CrewAI logo

CrewAI

Use ITM Platform MCP with CrewAI

FAQ

Frequently asked questions

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

Yes, absolutely. You can configure which ITM Platform 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 ITM Platform data and credentials are handled as safely as possible.

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