How to integrate Google Tasks MCP with Pydantic AI

This guide walks you through connecting Google Tasks to Pydantic AI using the Composio tool router. By the end, you'll have a working Google Tasks agent that can add a new task to your work list, list all tasks due this week, delete completed tasks from your shopping list through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Google Tasks account through Composio's Google Tasks MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Google Tasks is a to-do list and task management tool integrated into Gmail and Google Calendar. It helps you organize, track, and complete tasks across your Google ecosystem.

16 Tools5 Triggers

Introduction

This guide walks you through connecting Google Tasks to Pydantic AI using the Composio tool router. By the end, you'll have a working Google Tasks agent that can add a new task to your work list, list all tasks due this week, delete completed tasks from your shopping list through natural language commands.

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

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

Also integrate Google Tasks with

ChatGPTOpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenCodeCursorVS CodeOpenClawHermesCLIGoogle 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 Google Tasks
  • 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 Google Tasks 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 Google Tasks MCP server, and what's possible with it?

The Google Tasks MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Google Tasks account. It provides structured and secure access to your to-do lists and tasks, so your agent can create task lists, add or update tasks, reorganize and clean up your lists, and fetch or manage your action items automatically.

  • Intelligent task list management: Ask your agent to create new to-do lists, fetch existing ones, or remove lists you no longer need—all without manual clicks.
  • Automated task creation and updates: Let your agent add new tasks, set due dates, or update existing to-dos to keep your lists current and organized.
  • Efficient task organization and movement: Move tasks between lists, reorder them, or set parent/child relationships so your priorities always stay clear.
  • Fast cleanup and deletion: Direct your agent to clear completed tasks or delete specific items and lists, helping you declutter swiftly and securely.
  • Detailed task retrieval and review: Have your agent pull details on any task or list so you can review upcoming deadlines, notes, and status at a glance.

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

Supported Tools and Triggers

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

Batch Execute Google Tasks Operations

Executes multiple Google Tasks API operations in a single HTTP batch request and returns structured per-item results.

Clear tasks

Permanently and irreversibly clears all completed tasks from a specified Google Tasks list; this action is destructive, idempotent, and cannot be undone.

Create a task list

Creates a new task list with the specified title and returns a tasklist_id.

Delete task

Deletes a specified task from a Google Tasks list.

Delete task list

Permanently deletes an existing Google Task list, identified by `tasklist_id`, along with all its tasks; this operation is irreversible.

Get Task

Retrieve a specific Google Task.

Get task list

Retrieves a specific task list from the user's Google Tasks if the `tasklist_id` exists for the authenticated user.

Insert Task

Creates a new task in a given `tasklist_id`, optionally as a subtask of an existing `task_parent` or positioned after an existing `task_previous` sibling, where both `task_parent` and `task_previous` must belong to the same `tasklist_id` if specified.

List All Tasks Across All Lists

Tool to list all tasks across all of the user's task lists with optional filters.

List task lists

Fetches the authenticated user's task lists from Google Tasks; results may be paginated.

List Tasks

Retrieves tasks from a Google Tasks list; all date/time strings must be RFC3339 UTC, and `showCompleted` must be true if `completedMin` or `completedMax` are specified.

Move Task

Moves the specified task to another position in the task list or to a different task list.

Patch Task

Partially updates an existing task (identified by `task_id`) within a specific Google Task list (identified by `tasklist_id`), modifying only the provided attributes from `TaskInput` (e.

Patch task list

Updates the title of an existing Google Tasks task list.

Update Task (Full Replacement)

Tool to fully replace an existing Google Task using PUT method.

Update Task List

Updates the authenticated user's specified task list.

FRAMEWORKS

How to build Google Tasks MCP Agent with another framework

ChatGPT logo

ChatGPT

Use Google Tasks MCP with ChatGPT

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Google Tasks MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Google Tasks MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Google Tasks MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Google Tasks MCP with Claude Cowork

Codex logo

Codex

Use Google Tasks MCP with Codex

Cursor logo

Cursor

Use Google Tasks MCP with Cursor

OpenClaw logo

OpenClaw

Use Google Tasks MCP with OpenClaw

Hermes logo

Hermes

Use Google Tasks MCP with Hermes

CLI logo

CLI

Use Google Tasks MCP with CLI

Google ADK logo

Google ADK

Use Google Tasks MCP with Google ADK

LangChain logo

LangChain

Use Google Tasks MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Google Tasks MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Google Tasks MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Google Tasks MCP with LlamaIndex

CrewAI logo

CrewAI

Use Google Tasks MCP with CrewAI

OpenCode logo

OpenCode

Use Google Tasks MCP with OpenCode

VS Code logo

VS Code

Use Google Tasks MCP with VS Code

FAQ

Frequently asked questions

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

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

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