How to integrate Kintone MCP with Mastra AI

This guide walks you through connecting Kintone to Mastra AI 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 Mastra AI 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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Kintone is Cybozu's low-code business app platform for building team databases, workflows, and custom apps. It helps teams centralize work data, processes, and user administration without heavy custom development.

16 Tools

Introduction

This guide walks you through connecting Kintone to Mastra AI 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 Mastra AI 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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TL;DR

Here's what you'll learn:
  • Set up your environment so Mastra, OpenAI, and Composio work together
  • Create a Tool Router session in Composio that exposes Kintone tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Kintone tool definitions and attach them as a toolset
  • Build a Mastra agent that can reason, call tools, and return structured results
  • Run an interactive CLI where you can chat with your Kintone agent

What is Mastra AI?

Mastra AI is a TypeScript framework for building AI agents with tool support. It provides a clean API for creating agents that can use external services through MCP.

Key features include:

  • MCP Client: Built-in support for Model Context Protocol servers
  • Toolsets: Organize tools into logical groups
  • Step Callbacks: Monitor and debug agent execution
  • OpenAI Integration: Works with OpenAI models via @ai-sdk/openai

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 step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Node.js 18 or higher
  • A Composio account with an active API key
  • An OpenAI API key
  • Basic familiarity with TypeScript
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key.
  • You need credits or a connected billing setup to use the models.
  • Store the key somewhere safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Go to Settings and copy your API key.
  • This key lets your Mastra agent talk to Composio and reach Kintone through MCP.
3

Install dependencies

bash
npm install @composio/core @mastra/core @mastra/mcp @ai-sdk/openai dotenv

Install the required packages.

What's happening:

  • @composio/core is the Composio SDK for creating MCP sessions
  • @mastra/core provides the Agent class
  • @mastra/mcp is Mastra's MCP client
  • @ai-sdk/openai is the model wrapper for OpenAI
  • dotenv loads environment variables from .env
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_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
  • COMPOSIO_USER_ID tells Composio which user this session belongs to
  • OPENAI_API_KEY lets the Mastra agent call OpenAI models
5

Import libraries and validate environment

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey as string,
});
What's happening:
  • dotenv/config auto loads your .env so process.env.* is available
  • openai gives you a Mastra compatible model wrapper
  • Agent is the Mastra agent that will call tools and produce answers
  • MCPClient connects Mastra to your Composio MCP server
  • Composio is used to create a Tool Router session
6

Create a Tool Router session for Kintone

typescript
async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["kintone"],
    },
  );

  const composioMCPUrl = session.mcp.url;
  console.log("Kintone MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "kintone" for Kintone access
  • session.mcp.url is the MCP URL that Mastra's MCPClient will connect to
7

Configure Mastra MCP client and fetch tools

typescript
const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      nasdaq: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

console.log("Fetching MCP tools from Composio...");
const composioTools = await mcpClient.getTools();
console.log("Number of tools:", Object.keys(composioTools).length);
What's happening:
  • MCPClient takes an id for this client and a list of MCP servers
  • The headers property includes the x-api-key for authentication
  • getTools fetches the tool definitions exposed by the Kintone toolkit
8

Create the Mastra agent

typescript
const agent = new Agent({
    name: "kintone-mastra-agent",
    instructions: "You are an AI agent with Kintone tools via Composio.",
    model: "openai/gpt-5",
  });
What's happening:
  • Agent is the core Mastra agent
  • name is just an identifier for logging and debugging
  • instructions guide the agent to use tools instead of only answering in natural language
  • model uses openai("gpt-5") to configure the underlying LLM
9

Set up interactive chat interface

typescript
let messages: AiMessageType[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end.\n");

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: "> ",
});

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;
  }

  messages.push({
    id: crypto.randomUUID(),
    role: "user",
    content: trimmedInput,
  });

  console.log("\nAgent is thinking...\n");

  try {
    const response = await agent.generate(messages, {
      toolsets: {
        kintone: composioTools,
      },
      maxSteps: 8,
    });

    const { text } = response;

    if (text && text.trim().length > 0) {
      console.log(`Agent: ${text}\n`);
        messages.push({
          id: crypto.randomUUID(),
          role: "assistant",
          content: text,
        });
      }
    } catch (error) {
      console.error("\nError:", error);
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    console.log("\nSession ended.");
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
What's happening:
  • messages keeps the full conversation history in Mastra's expected format
  • agent.generate runs the agent with conversation history and Kintone toolsets
  • maxSteps limits how many tool calls the agent can take in a single run
  • onStepFinish is a hook that prints intermediate steps for debugging

Complete Code

Here's the complete code to get you started with Kintone and Mastra AI:

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({ apiKey: composioAPIKey as string });

async function main() {
  const session = await composio.create(composioUserID as string, {
    toolkits: ["kintone"],
  });

  const composioMCPUrl = session.mcp.url;

  const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      kintone: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "kintone-mastra-agent",
    instructions: "You are an AI agent with Kintone tools via Composio.",
    model: "openai/gpt-5",
  });

  let messages: AiMessageType[] = [];

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: "> ",
  });

  rl.prompt();

  rl.on("line", async (input: string) => {
    const trimmed = input.trim();
    if (["exit", "quit"].includes(trimmed.toLowerCase())) {
      rl.close();
      return;
    }

    messages.push({ id: crypto.randomUUID(), role: "user", content: trimmed });

    const { text } = await agent.generate(messages, {
      toolsets: { kintone: composioTools },
      maxSteps: 8,
    });

    if (text) {
      console.log(`Agent: ${text}\n`);
      messages.push({ id: crypto.randomUUID(), role: "assistant", content: text });
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main();

Conclusion

You've built a Mastra AI agent that can interact with Kintone through Composio's Tool Router. You can extend this further by:
  • Adding other toolkits like Gmail, Slack, or GitHub
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-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

LangChain logo

LangChain

Use Kintone MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Kintone MCP with Vercel AI SDK

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. Mastra AI 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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