How to integrate Clockify MCP with LlamaIndex

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Introduction

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

This guide will help you understand how to give your LlamaIndex 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.

Also integrate Clockify with

TL;DR

Here's what you'll learn:
  • Set your OpenAI and Composio API keys
  • Install LlamaIndex and Composio packages
  • Create a Composio Tool Router session for Clockify
  • Connect LlamaIndex to the Clockify MCP server
  • Build a Clockify-powered agent using LlamaIndex
  • Interact with Clockify through natural language

What is LlamaIndex?

LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools.

Key features include:

  • ReAct Agent: Reasoning and acting pattern for tool-using agents
  • MCP Tools: Native support for Model Context Protocol
  • Context Management: Maintain conversation context across interactions
  • Async Support: Built for async/await patterns

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
Add User to GroupTool to add a user to a user group in a Clockify workspace.
Create ClientTool to add a new client to a workspace.
Create New ProjectTool to create a new project in a Clockify workspace.
Create Shared ReportTool to create a shared report in Clockify.
Create TaskTool to add a new task to a project in Clockify.
Create Templates On WorkspaceTool to create templates on a Clockify workspace.
Create Time EntryTool to create a new time entry in a Clockify workspace.
Create User GroupTool to create a new user group in a workspace.
Create User Time EntryTool to create a time entry for another user in a Clockify workspace.
Create WebhookTool to create a new webhook in a workspace.
Create WorkspaceTool to create a new workspace in Clockify.
Delete ClientPermanently deletes a client from a Clockify workspace.
Delete ProjectTool to delete a project from a workspace.
Delete Shared ReportTool to delete a shared report from a workspace by ID.
Delete TagTool to delete a tag from a Clockify workspace.
Delete TaskTool to delete a task from a project in Clockify.
Delete TemplateTool to delete a template from a Clockify workspace.
Delete Time EntryTool to delete a time entry from a workspace by ID.
Delete User GroupTool to delete a user group from a workspace.
Delete User Time EntriesTool to delete multiple time entries for a user in a workspace.
Delete WebhookTool to delete a webhook from a workspace.
Duplicate Time EntryTool to duplicate an existing time entry in a Clockify workspace.
Filter Workspace UsersTool to filter users in a workspace by advanced criteria.
Find User's Team ManagersRetrieves the list of team managers assigned to a specific user in a Clockify workspace.
Generate Detailed ReportTool to generate a detailed time entry report with filtering and pagination.
Generate Expense ReportTool to generate a detailed expense report for a Clockify workspace.
Generate New Webhook TokenTool to generate a new webhook token.
Generate Summary ReportTool to generate a summary report for time entries in a Clockify workspace.
Generate Weekly ReportTool to generate a weekly time entry report for a workspace with grouped data.
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 IDRetrieves detailed information about a specific client in a Clockify workspace.
Get ClientsTool to list clients in a workspace.
Get Created EntitiesTool to retrieve created entities within a workspace (Experimental).
Get Currently Logged In User InfoTool to retrieve info about the authenticated user.
Get Deleted EntitiesTool to retrieve information about entities deleted within a date range (Experimental API).
Get HolidaysTool to retrieve all holidays for a workspace.
Get Holidays In PeriodTool to retrieve holidays in a specific period.
Get In Progress Time EntriesTool to retrieve all currently running time entries in a workspace.
Get member's profileTool to get a member's profile in a workspace.
Get ProjectTool to retrieve detailed information about a specific project by ID.
Get ProjectsTool to list projects in a workspace with filtering and pagination.
Get Shared ReportTool to retrieve a shared report by ID from Clockify.
Get Shared ReportsTool to retrieve all shared reports in a workspace.
Get Tag By IDTool to retrieve detailed information about a specific tag by ID in a Clockify workspace.
Get TagsTool to find and list tags in a workspace.
Get TaskRetrieves detailed information about a specific task in a Clockify project.
Get TasksTool to find all tasks on a specific project in a workspace.
Get Templates On WorkspaceTool to list all templates in a workspace.
Get Time EntriesTool to retrieve historical time entries for a user in a workspace with filters.
Get Time EntryTool to retrieve a specific time entry by ID from a workspace.
Get Updated EntitiesTool to retrieve entities that have been updated in a workspace (Experimental).
Get User GroupsTool to find all user groups in a workspace.
Get Webhook By IDRetrieves detailed information about a specific webhook in a Clockify workspace.
Get Webhook LogsTool to retrieve webhook logs for a specific webhook.
Get Workspace InfoRetrieves detailed information about a specific Clockify workspace.
List AssignmentsTool to retrieve all scheduling assignments in a workspace.
Remove User From GroupTool to remove a user from a group in Clockify.
Stop User TimerTool to stop a currently running timer for a user in a workspace.
Update ClientTool to update an existing client in a Clockify workspace.
Update ProjectTool to update an existing project in a Clockify workspace.
Update Project MembershipsTool to update project memberships in Clockify.
Update Project User Hourly RateTool to update a project user's billable rate.
Update Shared ReportTool to update an existing shared report in Clockify.
Update TagTool to update a tag in a Clockify workspace.
Update TaskTool to update an existing task on a project in Clockify.
Update Time EntriesTool to bulk update multiple time entries in a Clockify workspace.
Update Time EntryTool to update an existing time entry in a Clockify workspace.
Update User GroupTool to update an existing user group in a workspace.
Update User Hourly RateTool to update a user's hourly rate in a Clockify workspace.
Update WebhookTool to update a webhook in a workspace.
Update Workspace Hourly RateTool to update the workspace billable hourly rate.

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 you begin, make sure you have:
  • Python 3.8/Node 16 or higher installed
  • A Composio account with the API key
  • An OpenAI API key
  • A Clockify account and project
  • Basic familiarity with async Python/Typescript

Getting API Keys for OpenAI, Composio, and Clockify

OpenAI API key (OPENAI_API_KEY)
  • Go to the OpenAI dashboard
  • Create an API key if you don't have one
  • Assign it to OPENAI_API_KEY in .env
Composio API key and user ID
  • Log into the Composio dashboard
  • Copy your API key from Settings
    • Use this as COMPOSIO_API_KEY
  • Pick a stable user identifier (email or ID)
    • Use this as COMPOSIO_USER_ID

Installing dependencies

pip install composio-llamaindex llama-index llama-index-llms-openai llama-index-tools-mcp python-dotenv

Create a new Python project and install the necessary dependencies:

  • composio-llamaindex: Composio's LlamaIndex integration
  • llama-index: Core LlamaIndex framework
  • llama-index-llms-openai: OpenAI LLM integration
  • llama-index-tools-mcp: MCP client for LlamaIndex
  • python-dotenv: Environment variable management

Set environment variables

bash
OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id

Create a .env file in your project root:

These credentials will be used to:

  • Authenticate with OpenAI's GPT-5 model
  • Connect to Composio's Tool Router
  • Identify your Composio user session for Clockify access

Import modules

import asyncio
import os
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

Create a new file called clockify_llamaindex_agent.py and import the required modules:

Key imports:

  • asyncio: For async/await support
  • Composio: Main client for Composio services
  • LlamaIndexProvider: Adapts Composio tools for LlamaIndex
  • ReActAgent: LlamaIndex's reasoning and action agent
  • BasicMCPClient: Connects to MCP endpoints
  • McpToolSpec: Converts MCP tools to LlamaIndex format

Load environment variables and initialize Composio

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set in the environment")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment")

What's happening:

This ensures missing credentials cause early, clear errors before the agent attempts to initialise.

Create a Tool Router session and build the agent function

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["clockify"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")

    description = "An agent that uses Composio Tool Router MCP tools to perform Clockify actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Clockify actions.
    """
    return ReActAgent(tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True)

What's happening here:

  • We create a Composio client using your API key and configure it with the LlamaIndex provider
  • We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, clockify)
  • The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools
  • LlamaIndex will connect to this endpoint to dynamically discover and use the available Clockify tools.
  • The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.

Create an interactive chat loop

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

What's happening here:

  • We're creating a direct terminal interface to chat with your Clockify database
  • The LLM's responses are streamed to the CLI for faster interaction.
  • The agent uses context to maintain conversation history
  • You can type 'quit' or 'exit' to stop the chat loop gracefully
  • Agent responses and any errors are displayed in a clear, readable format

Define the main entry point

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")

What's happening here:

  • We're orchestrating the entire application flow
  • The agent gets built with proper error handling
  • Then we kick off the interactive chat loop so you can start talking to Clockify

Run the agent

npx ts-node llamaindex-agent.ts

When prompted, authenticate and authorise your agent with Clockify, then start asking questions.

Complete Code

Here's the complete code to get you started with Clockify and LlamaIndex:

import asyncio
import os
import signal
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["clockify"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")
    description = "An agent that uses Composio Tool Router MCP tools to perform Clockify actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Clockify actions.
    """
    return ReActAgent(
        tools=tools,
        llm=llm,
        description=description,
        system_prompt=system_prompt,
        verbose=True,
    );

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")

Conclusion

You've successfully connected Clockify to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways:
  • Tool Router dynamically exposes Clockify tools through an MCP endpoint
  • LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations
  • The agent becomes more capable without increasing prompt size
  • Async Python provides clean, efficient execution of agent workflows
You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter.

How to build Clockify MCP Agent with another framework

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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 LlamaIndex?

Yes, you can. LlamaIndex 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.

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