How to integrate Control d MCP with Autogen

This guide walks you through connecting Control d to AutoGen using the Composio tool router. By the end, you'll have a working Control d agent that can list all devices connected to your account, remove a device by its id, show known access ips for your network through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Control d account through Composio's Control d MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Get started for freeGet a demo
Control d logoControl d
Api Key

Control d is a customizable DNS filtering and traffic redirection platform. It helps you manage internet access, enforce policies, and monitor usage across devices and networks.

54 Tools

Introduction

This guide walks you through connecting Control d to AutoGen using the Composio tool router. By the end, you'll have a working Control d agent that can list all devices connected to your account, remove a device by its id, show known access ips for your network through natural language commands.

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

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

Also integrate Control d 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 Control d
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Control d tools
  • Run a live chat loop where you ask the agent to perform Control d 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 Control d MCP server, and what's possible with it?

The Control d MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Control d account. It provides structured and secure access to your DNS filtering and device management environment, so your agent can perform actions like managing devices, enforcing policies, retrieving analytics, and monitoring network access on your behalf.

  • Device inventory management: Easily list all devices on your account or remove specific devices by their identifier for streamlined device control.
  • Profile and rule administration: Direct your agent to delete profiles, custom rules, or schedules—helping you maintain and enforce up-to-date network policies.
  • Network access monitoring: Retrieve a list of known access IPs to keep tabs on which endpoints are connecting to your network infrastructure.
  • Analytics endpoints discovery: Quickly fetch available analytics storage regions and endpoints so you can integrate and analyze DNS traffic data efficiently.
  • Organization details access: Have the agent fetch and present your organization's account details for easy reference and auditing.

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 Control d 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 Control d 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 Control d 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 Control d session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["control_d"]
    )
    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 Control d 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 Control d assistant agent with MCP tools
    agent = AssistantAgent(
        name="control_d_assistant",
        description="An AI assistant that helps with Control d 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 Control d 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 Control d 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 Control d 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 Control d 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 Control d session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["control_d"]
    )
    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 Control d assistant agent with MCP tools
        agent = AssistantAgent(
            name="control_d_assistant",
            description="An AI assistant that helps with Control d 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 Control d 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 Control d 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 Control d, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

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

Delete Device by ID

Permanently delete a Control-D device/endpoint by its ID.

Delete Profile

Permanently deletes a Control D profile by its unique identifier (PK).

Delete Profile Rule by Rule ID

Delete a custom DNS rule from a Control D profile by its rule identifier (hostname/domain).

Delete Rule from Folder

Delete a custom DNS rule from a specific folder in a Control D profile.

Delete Profile Schedule

Tool to delete a specific schedule within a profile.

List Known Access IPs

List up to the latest 50 IP addresses that were used to query against a specific Device (resolver).

Get Analytics Endpoints

Tool to list analytics storage regions and their endpoints.

Get Analytics Levels

Tool to retrieve available analytics log levels for Control D devices.

Get Billing Payments

Tool to retrieve billing history of all payments made.

Get Billing Products

Retrieve all products currently activated on the Control D account.

Get Devices

Lists all Control D devices (endpoints) associated with the account.

Get Device Types

List all allowed device types in Control D.

Get IP

Tool to retrieve the current IP address and datacenter information for the API request.

Get Network Stats

Tool to retrieve network stats on available services in different POPs (Points of Presence).

Get Organization Members

Tool to view organization membership.

Get Organization Details

Tool to view the authenticated organization's details.

Get Sub-Organizations

Tool to view sub-organizations and their details.

Get Profiles

Tool to list all profiles associated with the authenticated account.

Get Profile Options

Retrieves all available configuration options for DNS profiles in Control D.

Get Profile by ID

Tool to retrieve details of a specific profile by its ID.

Get Profile Analytics

Retrieve analytics data for a Control D profile.

Get Profile Analytics Logs

Retrieves DNS query activity logs for a specific Control D profile.

Get Analytics Log Entry

Tool to retrieve a specific analytics log entry by its ID.

Get Profile Analytics Summary

Tool to fetch a summary of analytics data for a given profile.

Get Profile Analytics Top Domains

Tool to fetch top domains accessed within a specific profile.

Get Profile Top Services

Tool to fetch top services accessed within a profile.

Get Profile Filters

List all native (Control D curated) filters for a profile and their current states.

List External Filters for Profile

Tool to list third-party filters for a specific profile.

Get Profile Folders

List all rule folders (groups) within a Control D profile.

List Custom DNS Rules for Profile

Retrieve custom DNS rules for a Control D profile.

Get Specific Rule in Folder

Tool to retrieve a specific rule within a folder by its ID.

Get Profile Schedules

Tool to list schedules associated with a specific profile.

Get Profile Schedule

Tool to retrieve a specific schedule by its ID within a profile.

Get Profile Services

Tool to list services associated with a specific profile.

Get Proxies

Tool to retrieve the list of usable proxy locations that traffic can be redirected through.

Get Service Categories

List all available service categories in Control D.

List Services by Category

Retrieves all services within a specific ControlD service category.

Get Users

Retrieve the authenticated user's account information from Control D.

Create Device

Create a new device (DNS endpoint) in Control D.

Create Profile

Create a new blank profile or clone an existing one.

Create Custom DNS Rule

Create custom DNS rules for a profile to control domain resolution.

Create Custom Rules in Profile Folder

Tool to create custom rules within a specific folder for a profile.

Create Profile Schedule

Create a new time-based schedule within a Control D profile.

Modify Device

Modify an existing Control D device's settings.

Modify Organization

Modify organization settings such as name, contact details, website, and device limits.

Modify Profile

Modify an existing profile by its ID.

Bulk Update Profile Filters

Tool to bulk update filters on a specific profile.

Update External Filters for Profile

Tool to update external filters for a specific profile.

Modify Profile Filter

Modify the enabled state of a specific native filter on a profile.

Modify Custom Rule for Profile

Modify an existing custom DNS rule for a profile in Control D.

Update Custom Rule by Rule ID

Tool to update an existing custom rule by its ID.

Move Profile Rule to Folder

Tool to move a specific custom rule into a different folder.

Update Profile Schedule

Tool to update a specific schedule within a profile.

Modify Service for Profile

Tool to modify a specific service rule for a profile.

FRAMEWORKS

How to build Control d MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Control d MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Control d MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Control d MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Control d MCP with Claude Cowork

Codex logo

Codex

Use Control d MCP with Codex

OpenClaw logo

OpenClaw

Use Control d MCP with OpenClaw

Hermes logo

Hermes

Use Control d MCP with Hermes

CLI logo

CLI

Use Control d MCP with CLI

Google ADK logo

Google ADK

Use Control d MCP with Google ADK

LangChain logo

LangChain

Use Control d MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Control d MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Control d MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Control d MCP with LlamaIndex

CrewAI logo

CrewAI

Use Control d MCP with CrewAI

FAQ

Frequently asked questions

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

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

Start with Control d.It takes 30 seconds.

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

Start building
Customer stories

Teams ship real agents on Composio

GET STARTED FOR FREEBOOK A DEMO
agent.aiZoomLettaGleanHubSpotAWSWabi

Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati
Harsha Gaddipati
Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

Abhi Arya
Abhi Arya
Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave
Nirman Dave
CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu
Ryan Yu
Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

Tomisin Jenrola
Tomisin Jenrola
Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Jerome Leclanche
Jerome Leclanche
Co-Founder, Ingram Technologies