How to integrate Checkvist MCP with OpenAI Agents SDK

This guide walks you through connecting Checkvist to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Checkvist agent that can create your checklists, add tasks, search tasks, import task lists, and view task outlines through natural language commands. This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Checkvist account through Composio's Checkvist MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Checkvist logoCheckvist
Api Key

Checkvist is an online outliner and task manager for hierarchical lists, notes, tags, due dates, and assignees. Use it to plan projects, capture ideas, and organize work in clean nested lists.

16 Tools

Introduction

This guide walks you through connecting Checkvist to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Checkvist agent that can create your checklists, add tasks, search tasks, import task lists, and view task outlines through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Checkvist account through Composio's Checkvist MCP server.

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

Also integrate Checkvist with

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Checkvist
  • Configure an AI agent that can use Checkvist as a tool
  • Run a live chat session where you can ask the agent to perform Checkvist operations

What is OpenAI Agents SDK?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

What is the Checkvist MCP server, and what's possible with it?

The Checkvist MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Checkvist account. It provides structured and secure access to your checklists, tasks, tags, due dates, assignees, and task notes, so your agent can create lists, organize task hierarchies, search tasks, update assignments, and track task status on your behalf.

  • Checklist creation and organization: Have your agent create, rename, tag, review, or delete checklists, including archived and private lists.
  • Hierarchical task planning: Let the agent create individual tasks or import complete task hierarchies, then arrange subtasks, priorities, positions, due dates, tags, and assignees.
  • Task search and review: Instruct your agent to search across checklists by keywords, due dates, tags, status, or notes, and read checklist outlines or task trees.
  • Status and detail updates: Direct your agent to close, reopen, or invalidate tasks, update their content and placement, and add or remove tags.
  • Checklist restructuring and cleanup: Have your agent replace an existing task hierarchy with an updated outline or permanently remove tasks and their subtasks.

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:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Checkvist project
  • Some knowledge of Python or Typescript
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
3

Install dependencies

npm install @composio/openai-agents @openai/agents dotenv

Install the Composio SDK and the OpenAI Agents SDK.

4

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

5

Import dependencies

import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Checkvist.
6

Set up the Composio instance

dotenv.config();

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});
What's happening:
  • dotenv.config() loads your .env file so COMPOSIO_API_KEY and USER_ID are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.
7

Create a Tool Router session

// Create Tool Router session for Checkvist
const session = await composio.create(userId as string, {
  toolkits: ['checkvist'],
});
const mcpUrl = session.mcp.url;

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only checkvist.
  • The router checks the user's Checkvist connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Checkvist.
  • This approach keeps things lightweight and lets the agent request Checkvist tools only when needed during the conversation.
8

Configure the agent

// Configure agent with MCP tool
const agent = new Agent({
  name: 'Assistant',
  model: 'gpt-5',
  instructions:
    'You are a helpful assistant that can access Checkvist. Help users perform Checkvist operations through natural language.',
  tools: [
    hostedMcpTool({
      serverLabel: 'tool_router',
      serverUrl: mcpUrl,
      headers: { 'x-api-key': composioApiKey },
      requireApproval: 'never',
    }),
  ],
});
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Checkvist and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a hostedMcpTool that connects to the MCP server URL we created earlier.
  • The headers object includes the Composio API key for secure authentication with the MCP server.
  • requireApproval: 'never' means the agent can execute Checkvist operations without asking for permission each time, making interactions smoother.
9

Start chat loop and handle conversation

// Keep conversation state across turns
const conversationSession = new OpenAIConversationsSession();

// Simple CLI
const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: 'You: ',
});

console.log('\nComposio Tool Router session created.');
console.log('\nChat started. Type your requests below.');
console.log("Commands: 'exit', 'quit', or 'q' to end\n");

try {
  const first = await run(agent, 'What can you help me with?', { session: conversationSession });
  console.log(`Assistant: ${first.finalOutput}\n`);
} catch (e) {
  console.error('Error:', e instanceof Error ? e.message : e, '\n');
}

rl.prompt();

rl.on('line', async (userInput) => {
  const text = userInput.trim();

  if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
    console.log('Goodbye!');
    rl.close();
    process.exit(0);
  }

  if (!text) {
    rl.prompt();
    return;
  }

  try {
    const result = await run(agent, text, { session: conversationSession });
    console.log(`\nAssistant: ${result.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();
});

rl.on('close', () => {
  console.log('\n👋 Session ended.');
  process.exit(0);
});
What's happening:
  • The program prints a session URL that you visit to authorize Checkvist.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using run().
  • The responses are printed to the console.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Checkvist and OpenAI Agents SDK:

import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});

async function main() {
  // Create Tool Router session
  const session = await composio.create(userId as string, {
    toolkits: ['checkvist'],
  });
  const mcpUrl = session.mcp.url;

  // Configure agent with MCP tool
  const agent = new Agent({
    name: 'Assistant',
    model: 'gpt-5',
    instructions:
      'You are a helpful assistant that can access Checkvist. Help users perform Checkvist operations through natural language.',
    tools: [
      hostedMcpTool({
        serverLabel: 'tool_router',
        serverUrl: mcpUrl,
        headers: { 'x-api-key': composioApiKey },
        requireApproval: 'never',
      }),
    ],
  });

  // Keep conversation state across turns
  const conversationSession = new OpenAIConversationsSession();

  // Simple CLI
  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: ',
  });

  console.log('\nComposio Tool Router session created.');
  console.log('\nChat started. Type your requests below.');
  console.log("Commands: 'exit', 'quit', or 'q' to end\n");

  try {
    const first = await run(agent, 'What can you help me with?', { session: conversationSession });
    console.log(`Assistant: ${first.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();

  rl.on('line', async (userInput) => {
    const text = userInput.trim();

    if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
      console.log('Goodbye!');
      rl.close();
      process.exit(0);
    }

    if (!text) {
      rl.prompt();
      return;
    }

    try {
      const result = await run(agent, text, { session: conversationSession });
      console.log(`\nAssistant: ${result.finalOutput}\n`);
    } catch (e) {
      console.error('Error:', e instanceof Error ? e.message : e, '\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

This was a starter code for integrating Checkvist MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Checkvist.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.
TOOLS

Supported Tools

Every Checkvist action and event your agent gets out of the box.

Create Checklist

Create a Checkvist checklist with a name and optional visibility and tags.

Create Task

Create a task in a checklist, optionally under a parent and with tags, smart-syntax due date, position, priority, or assignees.

Delete Checklist

Mark a Checkvist checklist for deletion.

Delete Task

Permanently delete a Checkvist task and all of its child tasks.

Get Checklist

Get one Checkvist checklist's metadata by ID.

Get Tasks Outline

Read a checklist as a recommended markdown task outline, with controls for closed tasks, depth, compact output, or top-level preview.

Get Tasks Page

Read one explicit 1-based page of a large Checkvist checklist.

Get Task Tree

Read one Checkvist task and its subtasks as a markdown outline, optionally including closed items or notes and limiting depth.

Import Tasks

Create multiple hierarchical tasks from Checkvist indented text.

List Checklists

List checklists available to the authenticated Checkvist user, optionally including archived lists or omitting statistics for a faster response.

Replace Tasks

Delete every existing task in a checklist, then replace the hierarchy from Checkvist indented text or OPML.

Search Tasks

Search tasks across the user's Checkvist checklists using words and operators for due date (^ or due:), tag (# or tag:), state (in:), and notes (has:note).

Set Task Status

Set a task's status to closed, reopened, or invalidated using Checkvist's dedicated status operations.

Update Checklist

Update an existing checklist's name, visibility, or complete tag set.

Update Task

Update task content, hierarchy, replacement tags, due date, position, priority, assignees, or smart-syntax parsing.

Update Task Tags

Add and remove task tags without replacing the complete tag set.

FAQ

Frequently asked questions

With a standalone Checkvist MCP server, the agents and LLMs can only access a fixed set of Checkvist tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Checkvist and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. OpenAI Agents SDK 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 Checkvist tools.

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

Start with Checkvist.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Checkvist tool your agent needs.Free to start.

Start building