How to integrate Amazing Marvin MCP with Pydantic AI

This guide walks you through connecting Amazing Marvin to Pydantic AI using the Composio tool router. By the end, you'll have a working Amazing Marvin agent that can create your tasks, complete tasks, manage projects, set reminders, and track your time through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Amazing Marvin account through Composio's Amazing Marvin MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Amazing Marvin is a personal productivity app for tasks, projects, habits, planning, time tracking, and rewards. It helps you build a flexible workflow that matches how you actually work.

10 Tools

Introduction

This guide walks you through connecting Amazing Marvin to Pydantic AI using the Composio tool router. By the end, you'll have a working Amazing Marvin agent that can create your tasks, complete tasks, manage projects, set reminders, and track your time through natural language commands.

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

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

Also integrate Amazing Marvin 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 Amazing Marvin
  • 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 Amazing Marvin 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 Amazing Marvin MCP server, and what's possible with it?

The Amazing Marvin MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Amazing Marvin account. It provides structured and secure access to your tasks, projects, planning items, reminders, labels, and time tracking, so your agent can create and complete tasks, organize projects, manage reminders, review plans, and track time on your behalf.

  • Task and project management: Have your agent create tasks and projects with schedules, priorities, estimates, notes, labels, and project organization, or mark finished tasks complete.
  • Planning and workload review: Let the agent list open items, check what is scheduled for a specific date, or review work due by a chosen date.
  • Reminder management: Direct your agent to review scheduled reminders, set mobile push reminders, replace existing reminders, or delete reminders you no longer need.
  • Time tracking control: Instruct your agent to check which task is currently being tracked, start tracking time for a task, or stop the active timer.
  • Category and label organization: Have your agent list your available categories or labels, then use them to organize new tasks and projects.

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

Complete Task

Mark one task complete using Amazing Marvin's experimental completion endpoint.

Create Project

Create a project with optional hierarchy, planning, priority, estimate, labels, and notes.

Create Task

Create a task with optional scheduling, organization, estimate, and note fields; title autocompletion is enabled by default.

Delete Reminders

Permanently delete only the specified Amazing Marvin reminders by exact ID.

Get Current Time Tracking

Return the task currently being time-tracked, or tracked=false when no timer is active.

List Categories or Labels

List categories or labels so their IDs can be used when creating and organizing Amazing Marvin tasks and projects.

List Planning Items

List open child items, items scheduled for a date, or items due by a date; choose one view per call.

List Reminders

List all currently scheduled Amazing Marvin reminders.

Set Reminders

Create or replace one or more mobile push reminders using caller-supplied reminder IDs.

Set Time Tracking

Start or stop time tracking for one task.

FRAMEWORKS

How to build Amazing Marvin MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Amazing Marvin MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Amazing Marvin MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Amazing Marvin MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Amazing Marvin MCP with Claude Cowork

Codex logo

Codex

Use Amazing Marvin MCP with Codex

OpenClaw logo

OpenClaw

Use Amazing Marvin MCP with OpenClaw

Hermes logo

Hermes

Use Amazing Marvin MCP with Hermes

CLI logo

CLI

Use Amazing Marvin MCP with CLI

Google ADK logo

Google ADK

Use Amazing Marvin MCP with Google ADK

LangChain logo

LangChain

Use Amazing Marvin MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Amazing Marvin MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Amazing Marvin MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Amazing Marvin MCP with LlamaIndex

CrewAI logo

CrewAI

Use Amazing Marvin MCP with CrewAI

FAQ

Frequently asked questions

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

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

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