# How to integrate Chatwork MCP with LangChain

```json
{
  "title": "How to integrate Chatwork MCP with LangChain",
  "toolkit": "Chatwork",
  "toolkit_slug": "chatwork",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/chatwork/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/chatwork/framework/langchain.md",
  "updated_at": "2026-05-06T08:05:36.480Z"
}
```

## Introduction

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.

## Also integrate Chatwork with

- [OpenAI Agents SDK](https://composio.dev/toolkits/chatwork/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/chatwork/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/chatwork/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/chatwork/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/chatwork/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/chatwork/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/chatwork/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/chatwork/framework/cli)
- [Google ADK](https://composio.dev/toolkits/chatwork/framework/google-adk)
- [Vercel AI SDK](https://composio.dev/toolkits/chatwork/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/chatwork/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/chatwork/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/chatwork/framework/crew-ai)

## 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.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `CHATWORK_CHATWORK_DELETE_MESSAGE` | Delete Message | This tool allows you to delete a specific message from a chatwork room by calling the delete endpoint at https://api.chatwork.com/v2/rooms/{room id}/messages/{message id}. it requires authentication using a chatwork api token provided in the x-chatworktoken header, and the necessary permissions to delete messages in the specified room. |
| `CHATWORK_GET_CHATWORK_CONTACTS` | Get Chatwork Contacts | This tool retrieves a list of all contacts from chatwork. it is a fundamental tool that fetches all contact information such as account id, room id, name, chatwork id, organization details, department, and avatar image url, without needing additional parameters beyond authentication. |
| `CHATWORK_GET_FILE` | Get Chatwork File | This tool retrieves information about a specific file in a chat room. the api endpoint get /v2/rooms/{room id}/files/{file id} provides file details such as file id, account id, message id, filename, filesize, upload time, and download url, which are useful for retrieving file metadata, verifying file existence, and managing file sharing within chatwork. |
| `CHATWORK_GET_MY_STATUS` | Get My Chatwork Status | This tool retrieves the current status of the authenticated user, including unread message counts and task status. it provides a quick overview of unread messages, mentions, and tasks, making it valuable for monitoring chatwork activity and building automation workflows. |
| `CHATWORK_GET_ROOM_MEMBERS` | Get Room Members | This tool retrieves a list of all members in a specified chatwork room using the endpoint get /rooms/{room id}/members. it provides essential details like account id, role, name, chatwork id, organization id, and organization name, complementing the existing suite of room management tools. |
| `CHATWORK_GET_ROOM_MESSAGES` | Get Room Messages | This tool retrieves messages from a specific chatwork room using the get https://api.chatwork.com/v2/rooms/{room id}/messages endpoint. it requires a room id parameter and an optional force flag to refresh the cache by retrieving the 100 newest messages. |
| `CHATWORK_GET_ROOMS` | Get Chatwork Rooms | This tool retrieves a list of all chat rooms associated with the authenticated chatwork account. it includes group chats, direct chats, and personal chats, and does not require any additional parameters beyond authentication. |
| `CHATWORK_UPLOAD_FILE` | Upload File to Chatwork Room | This tool allows users to upload files to a specific chatwork room. it enables file sharing functionality within the chatwork platform by providing an endpoint to upload files (along with an optional message) to a given room. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Chatwork MCP server is an implementation of the Model Context Protocol that connects your AI agent to Chatwork. It provides structured and secure access so your agent can perform Chatwork operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

No description provided.

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

No description provided.
```python
pip install composio-langchain langchain-mcp-adapters langchain python-dotenv
```

```typescript
npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv
```

### 3. Set up environment variables

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
```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
```

### 4. Import dependencies

No description provided.
```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
```

```typescript
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();
```

### 5. Initialize Composio client

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
```python
async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
```

```typescript
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()
    });
```

### 6. Create a Tool Router session

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
```python
# Create Tool Router session for Chatwork
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['chatwork']
)

url = session.mcp.url
```

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

const url = session.mcp.url;
```

### 7. Configure the agent with the MCP URL

No description provided.
```python
client = MultiServerMCPClient({
    "chatwork-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
```

```typescript
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 });
```

### 8. Set up interactive chat interface

No description provided.
```python
conversation_history = []

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

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ['exit', 'quit', 'bye']:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
```

```typescript
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);
    });
```

### 9. Run the application

No description provided.
```python
if __name__ == "__main__":
    asyncio.run(main())
```

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

## Complete Code

```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['chatwork']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "chatwork-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Chatwork related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

if __name__ == "__main__":
    asyncio.run(main())
```

```typescript
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.

## How to build Chatwork MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/chatwork/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/chatwork/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/chatwork/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/chatwork/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/chatwork/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/chatwork/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/chatwork/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/chatwork/framework/cli)
- [Google ADK](https://composio.dev/toolkits/chatwork/framework/google-adk)
- [Vercel AI SDK](https://composio.dev/toolkits/chatwork/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/chatwork/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/chatwork/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/chatwork/framework/crew-ai)

## Related Toolkits

- [Gmail](https://composio.dev/toolkits/gmail) - Gmail is Google's email service with powerful spam protection, search, and G Suite integration. It keeps your inbox organized and makes communication fast and reliable.
- [Outlook](https://composio.dev/toolkits/outlook) - 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](https://composio.dev/toolkits/slack) - 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](https://composio.dev/toolkits/gong) - Gong is a platform for video meetings, call recording, and team collaboration. It helps teams capture conversations, analyze calls, and turn insights into action.
- [Microsoft teams](https://composio.dev/toolkits/microsoft_teams) - Microsoft Teams is a collaboration platform that combines chat, meetings, and file sharing within Microsoft 365. It keeps distributed teams connected and productive through seamless virtual communication.
- [Slackbot](https://composio.dev/toolkits/slackbot) - Slackbot is a conversational automation tool for Slack that handles reminders, notifications, and automated responses. It boosts team productivity by streamlining onboarding, answering FAQs, and managing timely alerts—all right inside Slack.
- [2chat](https://composio.dev/toolkits/_2chat) - 2chat is an API platform for WhatsApp and multichannel text messaging. It streamlines chat automation, group management, and real-time messaging for developers.
- [Agent mail](https://composio.dev/toolkits/agent_mail) - Agent mail provides AI agents with dedicated email inboxes for sending, receiving, and managing emails. It empowers agents to communicate autonomously with people, services, and other agents—no human intervention needed.
- [Basecamp](https://composio.dev/toolkits/basecamp) - Basecamp is a project management and team collaboration tool by 37signals. It helps teams organize tasks, share files, and communicate efficiently in one place.
- [Clickmeeting](https://composio.dev/toolkits/clickmeeting) - ClickMeeting is a cloud-based platform for running online meetings and webinars. It helps businesses and individuals host, manage, and engage virtual audiences with ease.
- [Confluence](https://composio.dev/toolkits/confluence) - Confluence is Atlassian's team collaboration and knowledge management platform. It helps your team organize, share, and update documents and project content in one secure workspace.
- [Dailybot](https://composio.dev/toolkits/dailybot) - DailyBot streamlines team collaboration with chat-based standups, reminders, and polls. It keeps work flowing smoothly in your favorite messaging platforms.
- [Dialmycalls](https://composio.dev/toolkits/dialmycalls) - Dialmycalls is a mass notification service for sending voice and text messages to contacts. It helps teams and organizations quickly broadcast urgent alerts and updates.
- [Dialpad](https://composio.dev/toolkits/dialpad) - Dialpad is a cloud-based business phone and contact center system for teams. It unifies voice, video, messaging, and meetings across your devices.
- [Discord](https://composio.dev/toolkits/discord) - Discord is a real-time messaging and VoIP platform for communities and teams. It lets users chat, share media, and collaborate across public and private channels.
- [Discordbot](https://composio.dev/toolkits/discordbot) - Discordbot is an automation tool for Discord servers that handles moderation, messaging, and user engagement. It helps communities run smoothly by automating routine and complex tasks.
- [Echtpost](https://composio.dev/toolkits/echtpost) - Echtpost is a secure digital communication platform for encrypted document and message exchange. It ensures confidential data stays private and protected during transmission.
- [Egnyte](https://composio.dev/toolkits/egnyte) - Egnyte is a cloud-based platform for secure file sharing, storage, and governance. It helps teams collaborate efficiently while maintaining data compliance and security.
- [Google Meet](https://composio.dev/toolkits/googlemeet) - Google Meet is a secure video conferencing platform for virtual meetings, chat, and screen sharing. It helps teams connect, collaborate, and communicate seamlessly from anywhere.
- [Heartbeat](https://composio.dev/toolkits/heartbeat) - Heartbeat is a plug-and-play platform for building and managing online communities. It helps you organize users, channels, events, and discussions in one place.

## Frequently Asked Questions

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

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.

### Can I use Tool Router MCP with LangChain?

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.

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

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.

### How safe is my data with Composio Tool Router?

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.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)