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How to integrate Timely MCP with Pydantic AI

Connect Pydantic AI to Timely MCP. Get your timely account billing details, set up webhook for new time entries, and more using natural language, with authentication handled for you.

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Timely is an automatic time-tracking platform that seamlessly records work across apps, calendars, and devices. It helps you create detailed timesheets and gain productivity insights without manual input.

41 Tools

Introduction

This guide walks you through connecting Timely to Pydantic AI using the Composio tool router. By the end, you'll have a working Timely agent that can create and filter reports, log time events, manage clients and projects, organize labels and teams, and check user capacity through natural language commands.

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

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

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

The Timely MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Timely account. It provides structured and secure access to your time-tracking data, so your agent can perform actions like retrieving account information, managing webhooks, and integrating time logs with other workflows on your behalf.

  • Account information retrieval: Instantly fetch up-to-date details about your Timely account, including billing, activity, and user info, for streamlined reporting or troubleshooting.
  • Automated webhook setup: Direct your agent to create new webhooks for your account, enabling real-time integration with external apps and automated event notifications.
  • Seamless workflow automation: Connect Timely events to other services or agents by configuring webhooks, so you can automate time-tracking updates or project triggers.
  • Centralized time management: Allow your agent to coordinate between Timely and your other productivity tools by securely accessing and sharing account data as needed.

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

Create Client

Tool to create a new client in the specified Timely account.

Create Day Locking

Create day locking entries for specified users and dates in a Timely account, setting them to locked or unlocked.

Create Label

Tool to create a new label in the specified Timely account.

Create report

Tool to generate reports for a Timely account with optional filters.

Create Team

Tool to create a new team in the specified Timely account.

Create Webhook

Tool to create a new webhook for the specified account.

Delete a label

Tool to delete a label by ID from a Timely account.

Delete a team

Tool to delete a team by its ID.

Delete Webhook

Tool to delete an existing webhook by its ID.

Filter reports

Tool to filter Timely reports based on date range, users, projects, labels, teams, and billing status.

Get activities

Tool to retrieve all activities (audit trail) for a Timely account.

Get Client

Tool to retrieve details of a specific client by its ID.

Get current user's permissions

Retrieve the authenticated user's permissions for a specified Timely account to check what actions they can perform.

Get current user

Tool to retrieve the currently authenticated user.

Retrieve a label

Retrieve a label by ID from a Timely account, including its name and parent relationship.

Get project

Tool to retrieve a single project by its ID.

Retrieve a team

Tool to retrieve details of a specific team by its ID.

Retrieve a user

Tool to retrieve a user by ID from a Timely account.

Get user capacities

Tool to retrieve capacity information for a specific user in a Timely account.

Get user permissions

Retrieve a specified user's permissions in a Timely account by user ID, to check what actions that user can perform.

Get Webhook

Tool to retrieve a specific webhook by its ID.

List accounts

Retrieve all accessible Timely accounts for the authenticated user.

List clients

Tool to list all clients in a Timely account with optional filtering and sorting.

List events

List events (time entries) in a Timely account with optional date, user, and project filters.

List forecasts

Tool to list all forecasts (tasks) in a Timely account with optional date filtering.

List labels

Tool to list all labels in a Timely account.

List project events

Tool to list all events (time entries) for a specific project in Timely.

List projects

Tool to list all projects in a Timely account with optional filtering and sorting.

List roles

Tool to list all available roles in a Timely account.

List teams

Tool to list all teams in the specified Timely account.

List user events

Tool to list all events (time entries) for a specific user in Timely.

List users

Tool to list all users in a Timely account with optional filtering and pagination.

List Webhooks

Tool to list all webhooks in the specified account.

Process bulk events

Create, update, or delete multiple time events in one bulk operation.

Retrieve an account

Tool to retrieve details of a specific account by its ID.

Update a client

Update an existing Timely client by ID, including its name, status, color, or external ID.

Update day locking settings

Tool to update day locking settings for specified users and dates.

Update a label

Tool to update a label by ID in a Timely account.

Update a project

Tool to update a project by ID in a Timely account.

Update a user

Tool to update a user by ID in a Timely account.

Update Webhook

Tool to update an existing webhook by ID.

FRAMEWORKS

How to build Timely MCP Agent with another framework

Claude Code logo

Claude Code

Use Timely MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Timely MCP with Claude Cowork

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Timely MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Timely MCP with Claude Agent SDK

Codex logo

Codex

Use Timely MCP with Codex

OpenClaw logo

OpenClaw

Use Timely MCP with OpenClaw

Hermes logo

Hermes

Use Timely MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Timely MCP with Atomic Agent

Google ADK logo

Google ADK

Use Timely MCP with Google ADK

LangChain logo

LangChain

Use Timely MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Timely MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Timely MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Timely MCP with LlamaIndex

CrewAI logo

CrewAI

Use Timely MCP with CrewAI

AutoGen logo

AutoGen

Use Timely MCP with AutoGen

FAQ

Frequently asked questions

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

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

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