How to integrate Toggl MCP with Pydantic AI

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Introduction

This guide walks you through connecting Toggl to Pydantic AI using the Composio tool router. By the end, you'll have a working Toggl agent that can start a new time entry for coding, list all clients in your workspace, get details of your current running timer through natural language commands.

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

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

Also integrate Toggl with

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

The Toggl MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Toggl account. It provides structured and secure access to your time tracking data, so your agent can perform actions like logging time entries, managing clients and projects, handling tags, and retrieving detailed activity reports on your behalf.

  • Automated time entry management: Let your agent start, stop, and create new time entries with precise details, making it easy to track your work hours hands-free.
  • Client and project organization: Easily add new clients or projects, fetch client details, or remove outdated clients to keep your workspace up to date and well-structured.
  • Real-time activity tracking: Ask your agent to retrieve the currently running time entry or list recent activities, so you always know where your time is going.
  • Tag management and organization: Automatically create or delete tags to categorize your time entries, helping you analyze how your time is spent across different tasks.
  • Comprehensive workspace administration: Have your agent create organizations, set up workspaces, and ensure all your time tracking infrastructure is ready to go without manual setup.

Supported Tools & Triggers

Tools
Create ClientTool to create a new client in a workspace.
Create GroupTool to create a new group in a Toggl organization.
Create InvitationTool to send invitations to join a Toggl organization.
Create OrganizationTool to create a new organization with a default workspace in Toggl Track.
Create ProjectCreates a new project in a Toggl workspace.
Create TagTool to create a new tag in a workspace.
Create Time EntryTool to create a new time entry in the specified workspace.
Add User to Workspace ProjectTool to add a user to workspace project users.
Delete Toggl ClientTool to delete a client in Toggl.
Delete GroupTool to delete a group from a Toggl organization.
Delete Project GroupTool to delete a project group from a Toggl workspace.
Delete SubscriptionTool to delete a webhook subscription in Toggl.
Delete TagDeletes a tag from a Toggl workspace.
Disable Weekly ReportTool to disable weekly report email notifications.
Bulk Edit Time EntriesTool to bulk edit multiple time entries in a workspace using JSON Patch operations.
Get All PlansTool to retrieve all available Toggl subscription plans and their features.
Get Client DetailsRetrieves detailed information about a specific client in Toggl Track by its client ID and workspace ID.
Get CountriesTool to retrieve all countries supported by Toggl.
Get Country SubdivisionsTool to retrieve all subdivisions (states, provinces, regions) for a specific country in Toggl Track.
Get CurrenciesTool to retrieve the list of all currencies supported by Toggl Track.
Get Current Time EntryRetrieves the currently running time entry for the authenticated user.
Get Event FiltersRetrieve the list of supported event filters for Toggl webhooks.
Get JWKS KeysRetrieves the current JWKS (JSON Web Key Set) keyset used to sign JWT tokens.
List ClientsRetrieve a list of clients from a Toggl Track workspace with optional filtering by status and name.
Get My LocationRetrieves the authenticated user's last known location information including city, state, country, and coordinates.
Get My QuotaTool to retrieve API rate limit quota for the authenticated user.
Get Organization DetailsRetrieves detailed information about a specific Toggl organization including subscription plan, trial status, user count, and workspace settings.
Get Organization GroupsRetrieves all groups within a Toggl organization, including group members and workspace assignments.
Get Organization UsersRetrieves a list of users belonging to a Toggl organization.
Get Project DetailsTool to retrieve details of a specific project.
Get ProjectsTool to retrieve a list of projects from a Toggl workspace.
Get Public Subscription PlansTool to retrieve all publicly available subscription plans from Toggl.
Get Webhooks StatusTool to retrieve the Toggl Webhooks server status.
Get TagsRetrieve all tags in a Toggl workspace.
List TasksTool to list tasks in a workspace or within a specific project.
Get Time EntriesRetrieve time entries for the authenticated user with flexible filtering options.
Get Time EntryTool to retrieve a specific time entry by its ID.
Get Timezone OffsetsTool to retrieve all available timezone offsets from Toggl.
Get TimezonesTool to retrieve all available timezones supported by Toggl Track.
Get User ClientsRetrieves all clients accessible to the authenticated user across all their workspaces.
Get User PreferencesRetrieves the authenticated user's preferences including timezone, date/time formats, notification settings, and enabled alpha/experimental features.
Get User ProjectsTool to retrieve all projects for the authenticated user.
Get User TagsTool to retrieve tags associated with the current user.
Get User TasksRetrieve all tasks across all workspaces accessible to the authenticated user.
Get User WorkspacesTool to retrieve all workspaces the authenticated user belongs to.
Get Workspace DetailsRetrieves comprehensive details and settings for a specific Toggl workspace by ID.
Get Workspace LogoTool to get workspace logo.
Get Workspace PreferencesRetrieves workspace preferences including the initial pricing plan and whether start/end times are hidden.
Get Workspace UsersRetrieves all users who belong to a specific Toggl workspace.
Stop Time EntryTool to stop a running time entry in a workspace.
Disable Product EmailsTool to disable product emails for the authenticated user using a disable code.
Update TagTool to update an existing tag in a specified workspace.
Send Demo EmailTool to send a demo request email through Toggl's system.
Send Email to ContactTool to send an email to a contact via Toggl's smail service.
Send Smail MeetTool to send an email for meet.
Update ClientUpdates an existing client in a Toggl workspace.

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

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

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.

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 Toggl
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file

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

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 Toggl
  • MCPServerStreamableHTTP connects to the Toggl MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant

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 Toggl
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["toggl"],
    )
    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 Toggl 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

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
toggl_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[toggl_mcp],
    instructions=(
        "You are a Toggl assistant. Use Toggl tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Toggl endpoint
  • The agent uses GPT-5 to interpret user commands and perform Toggl operations
  • The instructions field defines the agent's role and behavior

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 Toggl.\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
  • Toggl API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns

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 Toggl 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 Toggl
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["toggl"],
    )
    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
    toggl_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[toggl_mcp],
        instructions=(
            "You are a Toggl assistant. Use Toggl 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 Toggl.\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 Toggl through Composio's Tool Router. With this setup, your agent can perform real Toggl 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 + Toggl for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.

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FAQ

What are the differences in Tool Router MCP and Toggl MCP?

With a standalone Toggl MCP server, the agents and LLMs can only access a fixed set of Toggl tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Toggl and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with Pydantic AI?

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 Toggl tools.

Can I manage the permissions and scopes for Toggl while using Tool Router?

Yes, absolutely. You can configure which Toggl 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.

How safe is my data with Composio Tool Router?

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 Toggl data and credentials are handled as safely as possible.

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