How to integrate Timely MCP with LangChain

This guide walks you through connecting Timely to LangChain using the Composio tool router. By the end, you'll have a working Timely agent that can get your timely account billing details, set up webhook for new time entries, retrieve account info for client project through natural language commands. This guide will help you understand how to give your LangChain 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.

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Timely

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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.

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Introduction

This guide will help you understand how to give your LangChain 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

OpenAI Agents SDK Claude Agent SDK Claude Code Claude Cowork Codex OpenClaw Hermes CLI Google ADK Vercel AI SDK Mastra AI LlamaIndex CrewAI

TL;DR

Here's what you'll learn:

Get and set up your OpenAI and Composio API keys
Connect your Timely project to Composio
Create a Tool Router MCP session for Timely
Initialize an MCP client and retrieve Timely tools
Build a LangChain agent that can interact with Timely
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 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:

Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step10 STEPS

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

npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters 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/core is the core agent framework
dotenv/config 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

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();

What's happening:

We're importing LangChain's MCP adapter and Composio SDK
The dotenv/config import loads environment variables from your .env file
This setup prepares the foundation for connecting LangChain with Timely functionality through MCP

Initialize Composio client

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

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 Timely tools
Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

const session = await composio.create(
    userId as string,
    {
        toolkits: ['timely']
    }
);

const url = session.mcp.url;

What's happening:

We're creating a Tool Router session that gives your agent access to Timely 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 Timely tools as needed

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "timely-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });

What's happening:

We're creating a MultiServerMCPClient that connects to our Timely MCP server via HTTP
The client is configured with a name and the URL from our Tool Router session
getTools() retrieves all available Timely tools that the agent can use
We're creating a LangChain agent using the GPT-5 model

Set up interactive chat interface

let conversationHistory: any[] = [];

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

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

rl.prompt();

rl.on('line', async (userInput: string) => {
    const trimmedInput = userInput.trim();

    if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
        console.log("\nGoodbye!");
        rl.close();
        process.exit(0);
    }

    if (!trimmedInput) {
        rl.prompt();
        return;
    }

    conversationHistory.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\n👋 Session ended.');
        process.exit(0);
    });

What's happening:

We initialize an empty conversationHistory list to maintain context across interactions
A readline interface is used to continuously accept 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 invoke() method with the full conversation history
Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully

Run the application

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});

What's happening:

We call the main() function to start the application

Complete Code

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

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['timely']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "timely-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Timely related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    rl.prompt();

    rl.on('line', async (userInput: string) => {
        const trimmedInput = userInput.trim();
        
        if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
            console.log("\nGoodbye!");
            rl.close();
            process.exit(0);
        }
        
        if (!trimmedInput) {
            rl.prompt();
            return;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\nSession ended.');
        process.exit(0);
    });
}

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});

Conclusion

You've successfully built a LangChain agent that can interact with Timely 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.

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

Tool to create a day locking entry that prevents editing of time entries for specific dates and users.

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

Tool to retrieve the current user's permissions for a specified account.

Get current user

Tool to retrieve the currently authenticated user.

Retrieve a label

Tool to retrieve a label by ID from a Timely account.

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

Tool to retrieve a user's permissions by their ID.

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

Tool to list all events (time entries) in a Timely account with optional filtering by date range, users, and projects.

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

Tool to create, update, or delete multiple events in a single bulk operation.

Retrieve an account

Tool to retrieve details of a specific account by its ID.

Update a client

Tool to update an existing client by ID in Timely.

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

OpenAI Agents SDK

Use Timely MCP with OpenAI Agents SDK

Claude Agent SDK

Use Timely MCP with Claude Agent SDK

Claude Code

Use Timely MCP with Claude Code

Claude Cowork

Use Timely MCP with Claude Cowork

Codex

Use Timely MCP with Codex

OpenClaw

Use Timely MCP with OpenClaw

Hermes

Use Timely MCP with Hermes

CLI

Use Timely MCP with CLI

Google ADK

Use Timely MCP with Google ADK

Vercel AI SDK

Use Timely MCP with Vercel AI SDK

Mastra AI

Use Timely MCP with Mastra AI

LlamaIndex

Use Timely MCP with LlamaIndex

CrewAI

Use Timely MCP with CrewAI

MORE TOOLKITS

Explore Other Toolkits

Toolkit marketplace

Google Sheets

Oauth2

Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly.

Notion

Oauth2Api Key

Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place.

Airtable

Oauth2Api Key

Airtable combines the flexibility of spreadsheets with the power of a database for easy project and data management. Teams use Airtable to organize, track, and collaborate with custom views and automations.

Asana

Oauth2

Asana is a collaborative work management platform for teams to organize and track projects. It streamlines teamwork, boosts productivity, and keeps everyone aligned on goals.

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. 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 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

Customer stories

Teams ship real agents on Composio

GET STARTED FOR FREE BOOK A DEMO

Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati

Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

Abhi Arya

Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave

CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu

Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

Tomisin Jenrola

Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Jerome Leclanche

Co-Founder, Ingram Technologies

How to integrate Timely MCP with LangChain

Connect Timely without auth hassles

Introduction

Also integrate Timely with

TL;DR

What is LangChain?

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

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

What is Composio SDK?

How the Composio SDK works

Step-by-step Guide

Prerequisites

Getting API Keys for OpenAI and Composio

Install dependencies

Set up environment variables

Import dependencies

Initialize Composio client

Create a Tool Router session

Configure the agent with the MCP URL

Set up interactive chat interface

Run the application

Complete Code

Conclusion

Supported Tools

How to build Timely MCP Agent with another framework

OpenAI Agents SDK

Claude Agent SDK

Claude Code

Claude Cowork

Codex

OpenClaw

Hermes

CLI

Google ADK

Vercel AI SDK

Mastra AI

LlamaIndex

CrewAI

Explore Other Toolkits

Google Sheets

Notion

Airtable

Asana

Frequently asked questions

What are the differences in Tool Router MCP and Timely MCP?+

Can I use Tool Router MCP with LangChain?+

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

How safe is my data with Composio Tool Router?+

Start with Timely.It takes 30 seconds.

Teams ship real agents on Composio