How to integrate Chatwork MCP with LangChain

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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

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 & Triggers

Tools
Create Chatwork RoomTool to create a new group chat room in Chatwork.
Create Room Invitation LinkTool to create an invitation link for a Chatwork room.
Create Task in Chatwork RoomTool to create a new task in a Chatwork room.
Delete MessageThis tool allows you to delete a specific message from a Chatwork room by calling the DELETE endpoint at https://api.
Delete or Leave Chatwork RoomTool to leave or delete a Chatwork room.
Delete Room LinkDelete the invitation link for a Chatwork room.
Get Chatwork ContactsThis tool retrieves a list of all contacts from Chatwork.
Get Chatwork File InformationTool to get information about a specific file in a chat room.
Get Incoming Contact RequestsTool to retrieve pending contact approval requests received by the authenticated user.
Get My Chatwork ProfileTool to retrieve the authenticated user's profile information including account details, organization, contact information, and avatar URL.
Get MessageTool to retrieve information about a specific message in a Chatwork room.
Get My Chatwork StatusThis tool retrieves the current status of the authenticated user, including unread message counts and task status.
Get My Chatwork TasksTool to retrieve the authenticated user's task list from Chatwork (up to 100 items).
Get Chatwork RoomRetrieves detailed information about a specific Chatwork room using the API endpoint GET /rooms/{room_id}.
Get Room FilesTool to get list of files in a chat room (up to 100 files).
Get Room Invitation LinkRetrieves the invitation link for a specified Chatwork room using the API endpoint GET /rooms/{room_id}/link.
Get Room MembersRetrieves a complete list of all members in a specified Chatwork room using the API endpoint GET /rooms/{room_id}/members.
Get Room Messages V2Tool to retrieve messages from a Chatwork room (up to 100 messages).
Get Chatwork RoomsTool to retrieve a list of all chat rooms the authenticated user belongs to.
Get Room TasksRetrieves a list of tasks from a Chatwork room.
Get TaskRetrieves detailed information about a specific task in a Chatwork room using the API endpoint GET /rooms/{room_id}/tasks/{task_id}.
Mark Messages as ReadTool to mark messages as read in a Chatwork room.
Mark Messages as UnreadTool to mark messages as unread in a Chatwork room.
Post MessageTool to post a new message to a Chatwork room.
Update MessageTool to update an existing message in a Chatwork room.
Update Chatwork RoomTool to update chat room information (name, icon, description).
Update Room Invitation LinkTool to update the invitation link settings for a Chatwork room.
Update Room MembersUpdates the complete member list of a Chatwork room with bulk assignment of member roles (admin, member, readonly).
Update Task StatusTool to update the completion status of a task in a Chatwork room.
Upload File to Chatwork RoomThis tool allows users to upload files to a specific Chatwork room.

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:

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

Step-by-step Guide

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

pip install composio-langchain langchain-mcp-adapters langchain python-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 is the core agent framework
  • python-dotenv 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

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()
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Chatwork functionality through MCP

Initialize Composio client

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")
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

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

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

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)
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
  • get_tools() 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

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")
What's happening:
  • We initialize an empty conversation_history list to maintain context across interactions
  • A while loop continuously accepts 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 ainvoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully

Run the application

if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • We call the main() function using asyncio.run() to start the application

Complete Code

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

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())

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.

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FAQ

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.

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