How to integrate Toggl MCP with LangChain

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Introduction

This guide walks you through connecting Toggl to LangChain 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 LangChain 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:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Toggl project to Composio
  • Create a Tool Router MCP session for Toggl
  • Initialize an MCP client and retrieve Toggl tools
  • Build a LangChain agent that can interact with Toggl
  • Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

  • Agent Framework: Build agents that can use tools and make decisions
  • MCP Integration: Connect to external services through Model Context Protocol adapters
  • Memory Management: Maintain conversation history across interactions
  • Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

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  • Client and project organization: Easily add new clients or projects, fetch client details, or remove outdated clients to keep your workspace up to date and well-structured.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 this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI 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

pip install composio-langchain langchain-mcp-adapters langchain python-dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • composio-langchain provides Composio integration for LangChain
  • langchain-mcp-adapters enables MCP client connections
  • langchain is the core agent framework
  • python-dotenv loads environment variables

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio's API
  • COMPOSIO_USER_ID identifies the user for session management
  • OPENAI_API_KEY enables access to OpenAI's language models

Import dependencies

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Toggl functionality through MCP

Initialize Composio client

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
  • Creating a Composio instance that will manage our connection to Toggl tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

# Create Tool Router session for Toggl
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['toggl']
)

url = session.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
  • This approach allows the agent to dynamically load and use Toggl tools as needed

Configure the agent with the MCP URL

client = MultiServerMCPClient({
    "toggl-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Toggl MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • get_tools() retrieves all available Toggl tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model

Set up interactive chat interface

conversation_history = []

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

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ['exit', 'quit', 'bye']:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
What's happening:
  • We initialize an empty conversation_history list to maintain context across interactions
  • A while loop continuously accepts user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the ainvoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully

Run the application

if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • We call the main() function using asyncio.run() to start the application

Complete Code

Here's the complete code to get you started with Toggl and LangChain:

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['toggl']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "toggl-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Toggl related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

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

Conclusion

You've successfully built a LangChain agent that can interact with Toggl through Composio's Tool Router.

Key features of this implementation:

  • Dynamic tool loading through Composio's Tool Router
  • Conversation history maintenance for context-aware responses
  • Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

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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 LangChain?

Yes, you can. LangChain 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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