SIGN UPLOG IN
X (Twitter)LinkedInGitHubDiscordYouTube

How to integrate Timely MCP with Autogen

Connect Autogen 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.

Get started for freeGet a demo
Timely logoTimely
Oauth2

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 AutoGen 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 AutoGen 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

Claude CodeClaude CoworkOpenAI Agents SDKClaude Agent SDKCodexOpenClawHermesAtomic AgentGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAIPydantic AI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the required dependencies for Autogen and Composio
  • Initialize Composio and create a Tool Router session for Timely
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Timely tools
  • Run a live chat loop where you ask the agent to perform Timely operations

What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.

Key features include:

  • Multi-Agent Systems: Build collaborative agent workflows
  • MCP Workbench: Native support for Model Context Protocol tools
  • Streaming HTTP: Connect to external services through streamable HTTP
  • AssistantAgent: Pre-built agent class for tool-using assistants

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 step08 STEPS
1

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Timely account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
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 python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Timely via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

Create a .env file in your project folder.

What's happening:

  • COMPOSIO_API_KEY is required to talk to Composio
  • OPENAI_API_KEY is used by Autogen's OpenAI client
  • USER_ID is how Composio identifies which user's Timely connections to use
5

Import dependencies and create Tool Router session

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Timely session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["timely"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Timely tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

Configure MCP parameters for Autogen

python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.

What's happening:

  • url points to the Tool Router MCP endpoint from Composio
  • timeout is the HTTP timeout for requests
  • sse_read_timeout controls how long to wait when streaming responses
  • terminate_on_close=True cleans up the MCP server process when the workbench is closed
7

Create the model client and agent

python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Timely assistant agent with MCP tools
    agent = AssistantAgent(
        name="timely_assistant",
        description="An AI assistant that helps with Timely operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Timely tools from the workbench
8

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Timely related question or task to the agent.\n")

# Conversation loop
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")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Timely tools to call via MCP
  • agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
  • Typing exit, quit, or bye ends the loop

Complete Code

Here's the complete code to get you started with Timely and AutoGen:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Timely session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["timely"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Timely assistant agent with MCP tools
        agent = AssistantAgent(
            name="timely_assistant",
            description="An AI assistant that helps with Timely operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
        print("Ask any Timely related question or task to the agent.\n")

        # Conversation loop
        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")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You now have an Autogen assistant wired into Timely through Composio's Tool Router and MCP. From here you can:
  • Add more toolkits to the toolkits list, for example notion or hubspot
  • Refine the agent description to point it at specific workflows
  • Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Timely, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
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

Pydantic AI logo

Pydantic AI

Use Timely MCP with Pydantic AI

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. Autogen 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.

Start with Timely.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Timely tool your agent needs.Free to start.

Start building