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How to integrate Everhour MCP with LangChain

Connect LangChain to Everhour MCP. List all clients for this workspace, retrieve expense categories for new report, and more using natural language, with authentication handled for you.

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Everhour

Api Key

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.

51 Tools

Managed auth

Connect Everhour without auth hassles

We manage OAuth, API keys, token refresh, and scopes — you just build.

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Introduction

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 start timers, clock in and out, manage clients and projects, review timecards and timesheets, and list expenses and invoices 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.

For exact tool slugs and parameter tables, see the tool catalog in the Composio docs.

Also integrate Everhour with

Claude Code Claude Cowork OpenAI Agents SDK Claude Agent SDK Grok Bot Codex OpenClaw Hermes Atomic Agent Google ADK Vercel AI SDK Mastra AI LlamaIndex CrewAI Pydantic AI AutoGen

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.

Add Time

Add or upsert tracked time for a task, user, and date.

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

Delete a user's timecard for a specific date in Everhour.

Delete Time Record

Remove tracked time by record ID while retaining its history trail.

Discard Timesheet Approval

Withdraw the authenticated user's previously submitted timesheet approval request for a week.

List Expenses

List expense records logged by the authenticated user in Everhour.

Get Client by ID

Tool to retrieve a specific client by ID.

Get Current Timer

Get the authenticated Everhour user's current timer state.

Get Project

Tool to retrieve a specific project.

Get Projects Report

Return aggregated Everhour project time and financial metrics.

Get Section

Retrieve details of a specific section by its ID.

Get Task

Retrieve one native or integration-backed Everhour task by ID.

Get Task Time Records

Lists tracked-time records for an Everhour task with date and page filters.

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 User Time Records

List one Everhour user's tracked-time records.

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

List webhooks created with the Everhour API key, including their target URLs, subscribed events, active status, and timestamps.

List Invoices

Retrieves all invoices from your Everhour workspace.

List projects

Lists Everhour projects accessible to the authenticated user, with optional name, status, platform, and result-limit parameters.

List Project Tasks

List tasks in an Everhour project with optional filters and pagination.

List Project Time Records

List tracked-time records for an Everhour project.

List Sections

Lists all sections within a specific Everhour project.

List Tags

List all tags in the Everhour workspace.

List Team Members

Retrieves team members in the authenticated Everhour workspace, including IDs, names, roles, and statuses.

List Teams

Retrieves information about the authenticated team/workspace in Everhour.

List Team Time Records

List team time records for a date range; without dates, return only today.

List Timecards

Retrieves team timecards, including clock-in/out data and work hours, with optional date filtering.

List User Timecards

Retrieves a specific user's timecards, including clock-in/out data and work hours, 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

Permanently deletes an Everhour project by ID, including its tasks and associated time records.

Request Timesheet Approval

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

Search Tasks

Search accessible Everhour tasks, optionally including closed tasks.

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 Expense

Partially update an existing Everhour expense.

Update an existing project

Updates an existing Everhour project's settings by project ID, including its name or notes.

Update Timecard

Update or create a user's timecard for a specific date, setting clock-in, clock-out, or break duration.

Update Time Record

Update an existing tracked-time record by its record ID.

Update Webhook

Update an existing Everhour webhook's subscribed events or project filter.

FRAMEWORKS

How to build Everhour MCP Agent with another framework

Claude Code

Use Everhour MCP with Claude Code

Claude Cowork

Use Everhour MCP with Claude Cowork

OpenAI Agents SDK

Use Everhour MCP with OpenAI Agents SDK

Claude Agent SDK

Use Everhour MCP with Claude Agent SDK

Grok Bot

Use Everhour MCP with Grok Bot

Codex

Use Everhour MCP with Codex

OpenClaw

Use Everhour MCP with OpenClaw

Hermes

Use Everhour MCP with Hermes

Atomic Agent

Use Everhour MCP with Atomic Agent

Google ADK

Use Everhour MCP with Google ADK

Vercel AI SDK

Use Everhour MCP with Vercel AI SDK

Mastra AI

Use Everhour MCP with Mastra AI

LlamaIndex

Use Everhour MCP with LlamaIndex

CrewAI

Use Everhour MCP with CrewAI

Pydantic AI

Use Everhour MCP with Pydantic AI

AutoGen

Use Everhour MCP with AutoGen

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

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

Claude Code

Claude Cowork

OpenAI Agents SDK

Claude Agent SDK

Grok Bot

Codex

OpenClaw

Hermes

Atomic Agent

Google ADK

Vercel AI SDK

Mastra AI

LlamaIndex

CrewAI

Pydantic AI

AutoGen

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.