How to integrate Toggl Track MCP with Claude Agent SDK

This guide walks you through connecting Toggl Track to the Claude Agent SDK using the Composio tool router. By the end, you'll have a working Toggl Track agent that can track your time, create clients and projects, manage your tasks, and update time entries through natural language commands. This guide will help you understand how to give your Claude Agent SDK agent real control over a Toggl Track account through Composio's Toggl Track MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Toggl Track is a time tracking platform for recording work, organizing projects, and managing workspaces. It helps teams understand where time goes with clear reports, billable hours, and lightweight workflows.

21 Tools

Introduction

This guide walks you through connecting Toggl Track to the Claude Agent SDK using the Composio tool router. By the end, you'll have a working Toggl Track agent that can track your time, create clients and projects, manage your tasks, and update time entries through natural language commands.

This guide will help you understand how to give your Claude Agent SDK agent real control over a Toggl Track account through Composio's Toggl Track MCP server.

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

Also integrate Toggl Track with

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TL;DR

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

What is Claude Agent SDK?

The Claude Agent SDK is Anthropic's official framework for building AI agents powered by Claude. It provides a streamlined interface for creating agents with MCP tool support and conversation management.

Key features include:

  • Native MCP Support: Built-in support for Model Context Protocol servers
  • Permission Modes: Control tool execution permissions
  • Streaming Responses: Real-time response streaming for interactive applications
  • Context Manager: Clean async context management for sessions

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

The Toggl Track 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 Track account. It provides structured and secure access to your time entries, workspaces, projects, clients, tasks, and reports, so your agent can track work, manage timers, organize projects, update records, and produce time reports on your behalf.

  • Time entry management: Have your agent create, review, update, or delete time entries, including their descriptions, timing, billable status, tags, and work assignments.
  • Running timer control: Let the agent check your current timer, start a new running time entry, or stop work in progress.
  • Workspace and project organization: Direct your agent to list workspaces and manage projects, clients, and tasks used to organize tracked work.
  • Detailed time reporting: Instruct your agent to produce detailed time reports for a workspace and date range, grouped into useful report rows.
  • Bulk record updates: Have your agent apply the same description or billable status to multiple time entries at once.

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:
  • Composio API Key and Claude/Anthropic API Key
  • Primary know-how of Claude Agents SDK
  • A Toggl Track account
  • Some knowledge of Python
2

Getting API Keys for Claude/Anthropic and Composio

Claude/Anthropic API Key
  • Go to the Anthropic Console and create an API key. You'll need credits to use the models.
  • 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

npm install @anthropic-ai/claude-agent-sdk @composio/core dotenv

Install the Composio SDK and the Claude Agents SDK.

What's happening:

  • @composio/core provides Composio integration for Anthropic
  • @anthropic-ai/claude-agent-sdk is the core agent framework
  • dotenv/config loads environment variables
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
ANTHROPIC_API_KEY=your_anthropic_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID identifies the user for session management
  • ANTHROPIC_API_KEY authenticates with Anthropic/Claude
5

Import dependencies

import 'dotenv/config';
import readline from 'node:readline';
import { Composio } from '@composio/core';
import { query, type Options } from "@anthropic-ai/claude-agent-sdk";

dotenv.config();
What's happening:
  • We're importing all necessary libraries including the Claude Agent SDK and Composio
  • The dotenv.config() function loads environment variables from your .env file
  • This setup prepares the foundation for connecting Claude with Toggl Track functionality
6

Create a Composio instance and Tool Router session

async function chat() {
  const { COMPOSIO_API_KEY, USER_ID } = process.env;
  if (!COMPOSIO_API_KEY || !USER_ID) {
    throw new Error('COMPOSIO_API_KEY and USER_ID required in .env');
  }

  const composio = new Composio({ apiKey: COMPOSIO_API_KEY });

  // Create Tool Router session for Toggl Track
  const session = await composio.create(USER_ID, {
    toolkits: ['toggl_track'],
  });
  const mcpUrl = session?.mcp.url;
What's happening:
  • The function checks for the required COMPOSIO_API_KEY environment variable
  • We're creating a Composio instance using our API key
  • The create method creates a Tool Router session for Toggl Track
  • The returned url is the MCP server URL that your agent will use
7

Configure Claude Agent with MCP

const options: Options = {
  permissionMode: 'bypassPermissions',
  mcpServers: {
    composio: {
      type: 'http',
      url: mcpUrl,
      headers: { 'x-api-key': COMPOSIO_API_KEY }
    }
  },
  systemPrompt: 'You are a helpful assistant with access to Toggl Track tools via Composio.',
  maxTurns: 10,
};
What's happening:
  • We're configuring the Claude Agent options with the MCP server URL
  • permissionMode: 'bypassPermissions' allows the agent to execute operations without asking for permission each time
  • The system prompt instructs the agent that it has access to Toggl Track
  • maxTurns: 10 limits the conversation length to prevent excessive API usage
8

Create client and start chat loop

const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
  });

  console.log('\nChat started. Type "exit" to quit.\n');

  let isProcessing = false;

  async function ask(prompt: string) {
    isProcessing = true;
    rl.pause();

    process.stdout.write('Claude is thinking...');
    const stream = query({ prompt, options });

    let firstChunk = true;
    for await (const msg of stream) {
      const content = (msg as any).message?.content || (msg as any).content;
      if (Array.isArray(content)) {
        for (const block of content) {
          if (block.type === 'text' && block.text) {
            if (firstChunk) {
              process.stdout.write('\r\x1b[K');
              process.stdout.write('Claude: ');
              firstChunk = false;
            }
            process.stdout.write(block.text);
          }
        }
      }
    }
    process.stdout.write('\n\n');

    isProcessing = false;
    rl.resume();
    rl.prompt();
  }

  rl.on('line', async (line) => {
    if (isProcessing) return;

    const input = line.trim();
    if (input === 'exit') {
      rl.close();
      process.exit(0);
    }
    if (input) await ask(input);
    else rl.prompt();
  });

  await ask('What can you help me with?');
}
What's happening:
  • The readline interface is created to handle user input and output
  • The query function is used to send the user's input to the agent
  • The chat loop continues until the user types 'exit' or 'quit'
9

Run the application

try {
  await chat();
} catch (error) {
  console.error(error);
  process.exit(1);
}
What's happening:
  • The chat function is the entry point for the application
  • The try-catch block is used to handle any errors that occur

Complete Code

Here's the complete code to get you started with Toggl Track and Claude Agent SDK:

import 'dotenv/config';
import readline from 'node:readline';
import { Composio } from '@composio/core';
import { query, type Options } from "@anthropic-ai/claude-agent-sdk";

async function chat() {
  const { COMPOSIO_API_KEY, USER_ID } = process.env;
  if (!COMPOSIO_API_KEY || !USER_ID) {
    throw new Error('COMPOSIO_API_KEY and USER_ID required in .env');
  }

  const composio = new Composio({ apiKey: COMPOSIO_API_KEY });
  const session = await composio.create(USER_ID, {
    toolkits: ['toggl_track']
  });
  const mcp_url = session?.mcp.url;

  const options: Options = {
    permissionMode: 'bypassPermissions',
    mcpServers: {
      composio: {
        type: 'http',
        url: mcp_url,
        headers: { 'x-api-key': COMPOSIO_API_KEY }
      }
    },
    systemPrompt: 'You are a helpful assistant with access to Toggl Track tools via Composio.',
    maxTurns: 10,
  };

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
  });

  console.log('\nChat started. Type "exit" to quit.\n');

  let isProcessing = false;

  async function ask(prompt: string) {
    isProcessing = true;
    rl.pause();

    process.stdout.write('Claude is thinking...');
    const stream = query({ prompt, options });

    let firstChunk = true;
    for await (const msg of stream) {
      const content = (msg as any).message?.content || (msg as any).content;
      if (Array.isArray(content)) {
        for (const block of content) {
          if (block.type === 'text' && block.text) {
            if (firstChunk) {
              process.stdout.write('\r\x1b[K');
              process.stdout.write('Claude: ');
              firstChunk = false;
            }
            process.stdout.write(block.text);
          }
        }
      }
    }
    process.stdout.write('\n\n');

    isProcessing = false;
    rl.resume();
    rl.prompt();
  }

  rl.on('line', async (line) => {
    if (isProcessing) return;

    const input = line.trim();
    if (input === 'exit') {
      rl.close();
      process.exit(0);
    }
    if (input) await ask(input);
    else rl.prompt();
  });

  await ask('What can you help me with?');
}

try {
  await chat();
} catch (error) {
  console.error(error);
  process.exit(1);
}

Conclusion

You've successfully built a Claude Agent SDK agent that can interact with Toggl Track through Composio's Tool Router.

Key features:

  • Native MCP support through Claude's agent framework
  • Streaming responses for real-time interaction
  • Permission bypass for smooth automated workflows
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.
TOOLS

Supported Tools

Every Toggl Track action and event your agent gets out of the box.

Bulk Update Time Entries

Apply the same description and/or billable state to 1 to 100 Toggl Track time entries in one provider-native request.

Create Client

Create a client in a workspace for grouping projects.

Create Project

Create a project in a workspace for organizing time entries and tasks.

Create Task

Create a task under an active project for more specific time-entry assignment.

Create Time Entry

Create a running or completed time entry in a workspace; omit duration and stop to start a running timer.

Delete Client

Permanently delete one client from a Toggl Track workspace.

Delete Project

Delete one project while preserving its time entries by unassigning them from the project.

Delete Task

Permanently delete one task from its parent project.

Delete Time Entry

Permanently delete one time entry from a workspace.

Get Current Time Entry

Return the currently running time entry for the connected user, or indicate that no timer is running.

Get Current User

Return the connected Toggl Track user's identity and defaults, including the default workspace ID, without exposing credentials.

Get Time Entry

Get one time entry by ID, with optional related-entity and sharing metadata.

List Time Entries

List the connected user's time entries in an explicit date range, optionally including related project, task, user, and sharing metadata.

List Workspace Resources

Find projects, clients, tags, or tasks in a workspace and return their IDs for time-entry and resource-management tools.

List Workspaces

List workspaces accessible to the connected user and return the IDs needed by workspace-scoped tools, without exposing private tokens or calendar URLs.

Run Detailed Time Report

Return one page of detailed, grouped time-entry report rows for a workspace and date range, with an opaque cursor for the next page.

Stop Time Entry

Stop a currently running time entry and return its finalized timing data.

Update Client

Update a client's name, notes, or external reference.

Update Project

Update a project's name, client, active state, privacy, color, or date range.

Update Task

Update a task's name, completion state, estimate, assignee, or external reference.

Update Time Entry

Update the timing, description, assignment, billable state, or tags of an existing time entry.

FRAMEWORKS

How to build Toggl Track MCP Agent with another framework

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Claude Cowork

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Codex logo

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OpenClaw logo

OpenClaw

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Hermes logo

Hermes

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CLI

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Google ADK logo

Google ADK

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LangChain

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Vercel AI SDK logo

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Mastra AI logo

Mastra AI

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LlamaIndex logo

LlamaIndex

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CrewAI logo

CrewAI

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FAQ

Frequently asked questions

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

Yes, you can. Claude Agent 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 Toggl Track tools.

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

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