How to integrate Clockify MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Clockify to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Clockify agent that can list all my active workspaces, add a new client to marketing workspace, show all users on design team workspace, delete a client from the finance workspace through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Clockify account through Composio's Clockify MCP server.

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

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Clockify
  • Configure an AI agent that can use Clockify as a tool
  • Run a live chat session where you can ask the agent to perform Clockify operations

What is open-ai-agents-sdk?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

What is the Clockify MCP server, and what's possible with it?

The Clockify MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Clockify account. It provides structured and secure access to your team's time tracking data, so your agent can perform actions like managing clients, handling workspace users, setting up webhooks, and retrieving workspace details on your behalf.

  • Workspace user management: Let your agent list all users in a workspace, filter users by advanced criteria, or find team managers for more efficient team organization.
  • Client creation and deletion: Easily create new clients or remove existing ones from your workspace, streamlining project onboarding and cleanup.
  • Webhook automation: Enable your agent to create, delete, and manage webhooks for real-time notifications and integrations with other tools.
  • Workspace overview and navigation: Retrieve a list of all workspaces you belong to, empowering your agent to access and organize time tracking across multiple teams or projects.
  • Addon and webhook token management: Generate new webhook tokens and list all addon webhooks, ensuring secure and automated integrations with third-party services.

Supported Tools & Triggers

Tools
Create ClientTool to add a new client to a workspace.
Create WebhookTool to create a new webhook in a workspace.
Delete ClientTool to delete a client from a workspace.
Delete WebhookTool to delete a webhook from a workspace.
Filter Workspace UsersTool to filter users in a workspace by advanced criteria.
Find All Users On WorkspaceTool to list all users in a workspace.
Find User's Team ManagersTool to get managers of a user in a workspace.
Generate New Webhook TokenTool to generate a new webhook token.
Get All Addon WebhooksTool to list all webhooks for an addon in a workspace.
Get All My WorkspacesTool to list all workspaces the user belongs to.
Get All WebhooksTool to list all webhooks in a workspace.
Get Client By IDTool to get details of a client by id.
Get ClientsTool to list clients in a workspace.
Get Currently Logged In User InfoTool to retrieve info about the authenticated user.
Get HolidaysTool to retrieve all holidays for a workspace.
Get Holidays In PeriodTool to retrieve holidays in a specific period.
Get member's profileTool to get a member's profile in a workspace.
Get Webhook By IDTool to get details of a specific webhook.
Get Workspace InfoTool to get details of a specific workspace.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router 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 Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router 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:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Clockify project
  • Some knowledge of Python or Typescript

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

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

Import dependencies

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Clockify.

Set up the Composio instance

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a Clockify Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["clockify"]
)

mcp_url = session.mcp.url

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only clockify.
  • The router checks the user's Clockify connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Clockify.
  • This approach keeps things lightweight and lets the agent request Clockify tools only when needed during the conversation.

Configure the agent

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Clockify. "
        "Help users perform Clockify operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Clockify and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a HostedMCPTool that connects to the MCP server URL we created earlier.
  • The headers dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute Clockify operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
What's happening:
  • The program prints a session URL that you visit to authorize Clockify.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Clockify and open-ai-agents-sdk:

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["clockify"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Clockify. "
        "Help users perform Clockify operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())

Conclusion

This was a starter code for integrating Clockify MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Clockify.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

How to build Clockify MCP Agent with another framework

Claude Agent SDK

Claude Agent SDK

Use Clockify MCP with Claude Agent SDK

Google ADK

Google ADK

Use Clockify MCP with Google ADK

LangChain

LangChain

Use Clockify MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Clockify MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Clockify MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Clockify MCP with LlamaIndex

CrewAI

CrewAI

Use Clockify MCP with CrewAI

FAQ

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

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

Can I use Tool Router MCP with OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK 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 Clockify tools.

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

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

Used by agents from

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Context
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Entelligence
Rolai

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