How to integrate Kintone MCP with LangChain

This guide walks you through connecting Kintone to LangChain using the Composio tool router. By the end, you'll have a working Kintone agent that can list your users, create users and groups, manage department membership, change login codes, and check access through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Kintone account through Composio's Kintone MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Introduction

This guide walks you through connecting Kintone to LangChain using the Composio tool router. By the end, you'll have a working Kintone agent that can list your users, create users and groups, manage department membership, change login codes, and check access through natural language commands.

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

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

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OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Kintone project to Composio
  • Create a Tool Router MCP session for Kintone
  • Initialize an MCP client and retrieve Kintone tools
  • Build a LangChain agent that can interact with Kintone
  • 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 Kintone MCP server, and what's possible with it?

The Kintone MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Kintone account. It provides structured and secure access to your tenant directory, so your agent can manage users, organize departments and groups, update memberships, assign service access, and change login codes on your behalf.

  • User account management: Have your agent list, create, update, or permanently delete tenant users in batches.
  • Department and group organization: Let the agent list, create, update, or delete departments and static or dynamic groups.
  • Membership administration: Direct your agent to review department or group members, replace group membership lists, and update each user's department and static group memberships.
  • Access and service assignments: Instruct your agent to review a user's memberships and Kintone access, then replace service assignments for selected users.
  • Login code changes: Have your agent change login codes for selected users when accounts need to be renamed or reorganized.

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

Step by step10 STEPS
1

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
2

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.
3

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
4

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
5

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 Kintone functionality through MCP
6

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 Kintone tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding
7

Create a Tool Router session

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

const url = session.mcp.url;
What's happening:
  • We're creating a Tool Router session that gives your agent access to Kintone 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 Kintone tools as needed
8

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "kintone-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 Kintone MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • getTools() retrieves all available Kintone tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model
9

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 Kintone 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
10

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 Kintone 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: ['kintone']
        }
    );

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

Change User Login Codes

Irreversibly change the login codes of up to 100 Kintone users in one batch.

Create Departments

Create 1 to 100 Kintone departments in one batch.

Create Groups

Create 1 to 100 static or dynamic Kintone groups in one batch.

Create Users

Create 1 to 100 Kintone tenant users in one batch with a login code, password, and display name for each user.

Delete Users, Departments, or Groups

Permanently delete a non-empty batch of Kintone users, departments, or groups by exact code.

Get User Access

Get one user's department memberships, group memberships, and Kintone service assignment in one read.

List Departments or Groups

List or filter Kintone departments or groups, one page at a time.

List Department or Group Members

List users belonging to a Kintone department or group, one page at a time.

List Users

List or filter tenant users by ID or login code, one page at a time.

Replace Group Users

Replace a Kintone static group's complete user membership list.

Replace User Departments

Replace the complete department membership lists for one to 100 Kintone users.

Replace User Groups

Replace a Kintone user's complete static-group membership list.

Set User Service Assignments

Replace Kintone service access for one to 100 users.

Update Departments

Update mutable fields for 1 to 100 existing Kintone departments, identified by exact department code.

Update Groups

Update the name and optional description of 1 to 100 existing Kintone groups, identified by exact group code.

Update Users

Update editable profile and primary-organization fields for 1 to 100 existing Kintone tenant users identified by login code.

FRAMEWORKS

How to build Kintone MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Kintone MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Kintone MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Kintone MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Kintone MCP with Claude Cowork

Codex logo

Codex

Use Kintone MCP with Codex

OpenClaw logo

OpenClaw

Use Kintone MCP with OpenClaw

Hermes logo

Hermes

Use Kintone MCP with Hermes

CLI logo

CLI

Use Kintone MCP with CLI

Google ADK logo

Google ADK

Use Kintone MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Kintone MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Kintone MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Kintone MCP with LlamaIndex

CrewAI logo

CrewAI

Use Kintone MCP with CrewAI

FAQ

Frequently asked questions

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

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

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