How to integrate Checkvist MCP with Autogen

This guide walks you through connecting Checkvist to AutoGen 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 AutoGen 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.

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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 AutoGen 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 AutoGen 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

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the required dependencies for Autogen and Composio
  • Initialize Composio and create a Tool Router session for Checkvist
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Checkvist tools
  • Run a live chat loop where you ask the agent to perform Checkvist operations

What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.

Key features include:

  • Multi-Agent Systems: Build collaborative agent workflows
  • MCP Workbench: Native support for Model Context Protocol tools
  • Streaming HTTP: Connect to external services through streamable HTTP
  • AssistantAgent: Pre-built agent class for tool-using assistants

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 step08 STEPS
1

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Checkvist account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
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

bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Checkvist via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

Create a .env file in your project folder.

What's happening:

  • COMPOSIO_API_KEY is required to talk to Composio
  • OPENAI_API_KEY is used by Autogen's OpenAI client
  • USER_ID is how Composio identifies which user's Checkvist connections to use
5

Import dependencies and create Tool Router session

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Checkvist session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["checkvist"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Checkvist tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

Configure MCP parameters for Autogen

python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.

What's happening:

  • url points to the Tool Router MCP endpoint from Composio
  • timeout is the HTTP timeout for requests
  • sse_read_timeout controls how long to wait when streaming responses
  • terminate_on_close=True cleans up the MCP server process when the workbench is closed
7

Create the model client and agent

python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Checkvist assistant agent with MCP tools
    agent = AssistantAgent(
        name="checkvist_assistant",
        description="An AI assistant that helps with Checkvist operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Checkvist tools from the workbench
8

Run the interactive chat loop

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

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

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

    if not user_input:
        continue

    print("\nAgent is thinking...\n")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Checkvist tools to call via MCP
  • agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
  • Typing exit, quit, or bye ends the loop

Complete Code

Here's the complete code to get you started with Checkvist and AutoGen:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Checkvist session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["checkvist"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Checkvist assistant agent with MCP tools
        agent = AssistantAgent(
            name="checkvist_assistant",
            description="An AI assistant that helps with Checkvist operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

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

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

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

            if not user_input:
                continue

            print("\nAgent is thinking...\n")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

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

Conclusion

You now have an Autogen assistant wired into Checkvist through Composio's Tool Router and MCP. From here you can:
  • Add more toolkits to the toolkits list, for example notion or hubspot
  • Refine the agent description to point it at specific workflows
  • Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Checkvist, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
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.

FRAMEWORKS

How to build Checkvist MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Checkvist MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Checkvist MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Checkvist MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Checkvist MCP with Claude Cowork

Codex logo

Codex

Use Checkvist MCP with Codex

OpenClaw logo

OpenClaw

Use Checkvist MCP with OpenClaw

Hermes logo

Hermes

Use Checkvist MCP with Hermes

CLI logo

CLI

Use Checkvist MCP with CLI

Google ADK logo

Google ADK

Use Checkvist MCP with Google ADK

LangChain logo

LangChain

Use Checkvist MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Checkvist MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Checkvist MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Checkvist MCP with LlamaIndex

CrewAI logo

CrewAI

Use Checkvist MCP with CrewAI

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. Autogen 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.

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