How to integrate Everhour MCP with LangChain

This guide walks you through connecting Everhour to LangChain using the Composio tool router. By the end, you'll have a working Everhour agent that can list all clients for this workspace, retrieve expense categories for new report, get your everhour user profile details through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Everhour account through Composio's Everhour MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Everhour

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Everhour is a time tracking and expense management platform for teams and individuals. Gain insight into hours, costs, and budgets for smarter planning and resource allocation.

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Introduction

This guide will help you understand how to give your LangChain agent real control over a Everhour account through Composio's Everhour MCP server.

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

Also integrate Everhour 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 Everhour project to Composio
Create a Tool Router MCP session for Everhour
Initialize an MCP client and retrieve Everhour tools
Build a LangChain agent that can interact with Everhour
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 Everhour MCP server, and what's possible with it?

The Everhour MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Everhour account. It provides structured and secure access to your time tracking, client, and expense data, so your agent can perform actions like listing clients, retrieving expenses, managing projects, and fetching user profiles on your behalf.

Comprehensive client management: Ask your agent to list, create, or delete clients to keep your workspace organized and up-to-date.
Expense tracking and review: Effortlessly retrieve all expenses or list available expense categories to monitor spending and streamline expense management.
Project and section insights: Have your agent fetch detailed information about specific projects or sections using their IDs for better resource planning.
Personalized user profile access: Enable your agent to fetch the authenticated user's profile for quick access to account details and preferences.
Webhook configuration overview: List all configured webhooks to monitor integrations and automate notifications within your Everhour environment.

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 Everhour 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 Everhour 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: ['everhour']
    }
);

const url = session.mcp.url;

What's happening:

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

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "everhour-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 Everhour MCP server via HTTP
The client is configured with a name and the URL from our Tool Router session
getTools() retrieves all available Everhour 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 Everhour 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 Everhour 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: ['everhour']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "everhour-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 Everhour 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 Everhour 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 Everhour action and event your agent gets out of the box.

Create Client

Creates a new client in Everhour for tracking billable work, invoicing, and project organization.

Delete a client

Tool to delete a client.

List Clients

Retrieves all clients in the Everhour workspace.

Clock In User

Tool to clock in a user for time tracking.

Clock Out User

Tool to clock out a user for time tracking.

Create Webhook

Tool to create a new webhook for event notifications in Everhour.

Delete Webhook

Tool to delete a webhook.

Delete a timecard

Tool to delete a timecard for a user on a specific date.

Discard Timesheet Approval

Tool to discard a pending timesheet approval request.

List Expenses

Lists expense records from your Everhour workspace.

Get Client by ID

Tool to retrieve a specific client by ID.

Get Project

Tool to retrieve a specific project.

Get Section

Retrieve details of a specific section by its ID.

Get Timecard

Tool to retrieve a specific timecard for a user on a date.

Get Authenticated User Profile

Tool to retrieve profile information of the authenticated user.

Get Webhook

Retrieve details of a specific webhook by its ID.

List Expense Categories

Lists all expense categories available in your Everhour account.

List Webhooks

Lists all webhooks configured for the Everhour account.

List Invoices

Retrieves all invoices from your Everhour workspace.

List projects

List all Everhour projects accessible by the authenticated user.

List Sections

Lists all sections within a specific Everhour project.

List Tags

List all tags in the Everhour workspace.

List Team Members

Retrieves all team members in the authenticated Everhour workspace.

List Teams

Retrieves information about the authenticated team/workspace in Everhour.

List Timecards

Tool to retrieve all team timecards with optional date filtering.

List User Timecards

Tool to retrieve timecards for a specific user with optional date filtering.

List User Timesheets

Tool to retrieve timesheets for a specific user.

Create Project

Tool to create a new project in Everhour.

Delete a project

Tool to delete a project.

Request Timesheet Approval

Tool to request approval for a timesheet or approve a week (for admins).

Create Section

Tool to create a new section in a project.

Delete a section

Tool to delete a section.

Create Task

Creates a new task in an Everhour project.

Start Timer

Tool to start a new timer for a task.

Update Client

Tool to update an existing client in Everhour.

Update an existing project

Updates an existing Everhour project's settings.

Update Timecard

Tool to update a timecard for a user on a specific date.

Update Webhook

Tool to update an existing webhook configuration in Everhour.

FRAMEWORKS

How to build Everhour MCP Agent with another framework

OpenAI Agents SDK

Use Everhour MCP with OpenAI Agents SDK

Claude Agent SDK

Use Everhour MCP with Claude Agent SDK

Claude Code

Use Everhour MCP with Claude Code

Claude Cowork

Use Everhour MCP with Claude Cowork

Codex

Use Everhour MCP with Codex

OpenClaw

Use Everhour MCP with OpenClaw

Hermes

Use Everhour MCP with Hermes

CLI

Use Everhour MCP with CLI

Google ADK

Use Everhour MCP with Google ADK

Vercel AI SDK

Use Everhour MCP with Vercel AI SDK

Mastra AI

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LlamaIndex

Use Everhour MCP with LlamaIndex

CrewAI

Use Everhour 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 Everhour MCP server, the agents and LLMs can only access a fixed set of Everhour tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Everhour 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 Everhour tools.

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

Start with Everhour.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Everhour 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 Everhour MCP with LangChain

Connect Everhour without auth hassles

Introduction

Also integrate Everhour with

TL;DR

What is LangChain?

What is the Everhour 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 Everhour 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 Everhour MCP?+

Can I use Tool Router MCP with LangChain?+

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

How safe is my data with Composio Tool Router?+

Start with Everhour.It takes 30 seconds.

Teams ship real agents on Composio