How to integrate Chatwork MCP with LangChain

This guide walks you through connecting Chatwork to LangChain using the Composio tool router. By the end, you'll have a working Chatwork agent that can list all unread messages across rooms, upload meeting notes file to project room, get all members of marketing chat through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Chatwork account through Composio's Chatwork MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Chatwork

Api Key

Chatwork is a team communication platform with group chats, file sharing, and task management. It helps businesses boost collaboration and streamline productivity.

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Introduction

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

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

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

The Chatwork MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Chatwork account. It provides structured and secure access to your chats, contacts, files, and rooms, so your agent can perform actions like sending messages, managing tasks, retrieving files, and organizing team communications on your behalf.

Room and member management: Easily fetch all chat rooms, list members in any room, and keep your workspace organized by letting your agent handle the heavy lifting.
Smart message retrieval and deletion: Have your agent pull recent messages from any chat, search for important info, or even delete specific messages when needed.
File sharing and retrieval: Seamlessly upload files to any Chatwork room or retrieve details and download links for files already shared, making document collaboration a breeze.
Contact and status insights: Instantly get a list of all your Chatwork contacts or check your current unread messages and task status without switching tabs.
Automated task and notification workflows: Let your agent monitor unread messages, mentions, and tasks, helping you stay on top of communication and never miss an important update.

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 Chatwork 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 Chatwork 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: ['chatwork']
    }
);

const url = session.mcp.url;

What's happening:

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

Configure the agent with the MCP URL

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

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

Create Chatwork Room

Tool to create a new group chat room in Chatwork.

Create Room Invitation Link

Tool to create an invitation link for a Chatwork room.

Create Task in Chatwork Room

Tool to create a new task in a Chatwork room.

Delete Message

This tool allows you to delete a specific message from a Chatwork room by calling the DELETE endpoint at https://api.

Delete or Leave Chatwork Room

Tool to leave or delete a Chatwork room.

Delete Room Link

Delete the invitation link for a Chatwork room.

Get Chatwork Contacts

This tool retrieves a list of all contacts from Chatwork.

Get Chatwork File Information

Tool to get information about a specific file in a chat room.

Get Incoming Contact Requests

Tool to retrieve pending contact approval requests received by the authenticated user.

Get My Chatwork Profile

Tool to retrieve the authenticated user's profile information including account details, organization, contact information, and avatar URL.

Get Message

Tool to retrieve information about a specific message in a Chatwork room.

Get My Chatwork Status

This tool retrieves the current status of the authenticated user, including unread message counts and task status.

Get My Chatwork Tasks

Tool to retrieve the authenticated user's task list from Chatwork (up to 100 items).

Get Chatwork Room

Retrieves detailed information about a specific Chatwork room using the API endpoint GET /rooms/{room_id}.

Get Room Files

Tool to get list of files in a chat room (up to 100 files).

Get Room Invitation Link

Retrieves the invitation link for a specified Chatwork room using the API endpoint GET /rooms/{room_id}/link.

Get Room Members

Retrieves a complete list of all members in a specified Chatwork room using the API endpoint GET /rooms/{room_id}/members.

Get Room Messages V2

Tool to retrieve messages from a Chatwork room (up to 100 messages).

Get Chatwork Rooms

Tool to retrieve a list of all chat rooms the authenticated user belongs to.

Get Room Tasks

Retrieves a list of tasks from a Chatwork room.

Get Task

Retrieves detailed information about a specific task in a Chatwork room using the API endpoint GET /rooms/{room_id}/tasks/{task_id}.

Mark Messages as Read

Tool to mark messages as read in a Chatwork room.

Mark Messages as Unread

Tool to mark messages as unread in a Chatwork room.

Post Message

Tool to post a new message to a Chatwork room.

Update Message

Tool to update an existing message in a Chatwork room.

Update Chatwork Room

Tool to update chat room information (name, icon, description).

Update Room Invitation Link

Tool to update the invitation link settings for a Chatwork room.

Update Room Members

Updates the complete member list of a Chatwork room with bulk assignment of member roles (admin, member, readonly).

Update Task Status

Tool to update the completion status of a task in a Chatwork room.

Upload File to Chatwork Room

This tool allows users to upload files to a specific Chatwork room.

FRAMEWORKS

How to build Chatwork MCP Agent with another framework

OpenAI Agents SDK

Use Chatwork MCP with OpenAI Agents SDK

Claude Agent SDK

Use Chatwork MCP with Claude Agent SDK

Claude Code

Use Chatwork MCP with Claude Code

Claude Cowork

Use Chatwork MCP with Claude Cowork

Codex

Use Chatwork MCP with Codex

OpenClaw

Use Chatwork MCP with OpenClaw

Hermes

Use Chatwork MCP with Hermes

CLI

Use Chatwork MCP with CLI

Google ADK

Use Chatwork MCP with Google ADK

Vercel AI SDK

Use Chatwork MCP with Vercel AI SDK

Mastra AI

Use Chatwork MCP with Mastra AI

LlamaIndex

Use Chatwork MCP with LlamaIndex

CrewAI

Use Chatwork MCP with CrewAI

MORE TOOLKITS

Explore Other Toolkits

Toolkit marketplace

Gmail

Oauth2

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Outlook

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Outlook is Microsoft's email and calendaring platform for unified communications and scheduling. It helps users stay organized with powerful email, contacts, and calendar management.

Slack

Oauth2

Slack is a channel-based messaging platform for teams and organizations. It helps people collaborate in real time, share files, and connect all their tools in one place.

Gong

BasicOauth2

Gong is a platform for video meetings, call recording, and team collaboration. It helps teams capture conversations, analyze calls, and turn insights into action.

FAQ

Frequently asked questions

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

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

Start with Chatwork.It takes 30 seconds.

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

Connect Chatwork without auth hassles

Introduction

Also integrate Chatwork with

TL;DR

What is LangChain?

What is the Chatwork 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 Chatwork 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

Gmail

Outlook

Slack

Gong

Frequently asked questions

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

Can I use Tool Router MCP with LangChain?+

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

How safe is my data with Composio Tool Router?+

Start with Chatwork.It takes 30 seconds.

Teams ship real agents on Composio