How to integrate Control d MCP with CrewAI

Trusted by
AWS
Glean
Zoom
Airtable
GET STARTED FOR FREEGET A DEMO

30 min · no commitment · see it on your stack

Control d logo
CrewAI logo
divider

Introduction

This guide walks you through connecting Control d to CrewAI 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 CrewAI 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

TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Control d connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Control d
  • Build a conversational loop where your agent can execute Control d operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

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.

Supported Tools & Triggers

Tools
Delete Device by IDPermanently delete a Control-D device/endpoint by its ID.
Delete ProfilePermanently deletes a Control D profile by its unique identifier (PK).
Delete Profile Rule by Rule IDDelete a custom DNS rule from a Control D profile by its rule identifier (hostname/domain).
Delete Rule from FolderDelete a custom DNS rule from a specific folder in a Control D profile.
Delete Profile ScheduleTool to delete a specific schedule within a profile.
List Known Access IPsList up to the latest 50 IP addresses that were used to query against a specific Device (resolver).
Get Analytics EndpointsTool to list analytics storage regions and their endpoints.
Get Analytics LevelsTool to retrieve available analytics log levels for Control D devices.
Get Billing PaymentsTool to retrieve billing history of all payments made.
Get Billing ProductsRetrieve all products currently activated on the Control D account.
Get DevicesLists all Control D devices (endpoints) associated with the account.
Get Device TypesList all allowed device types in Control D.
Get IPTool to retrieve the current IP address and datacenter information for the API request.
Get Network StatsTool to retrieve network stats on available services in different POPs (Points of Presence).
Get Organization MembersTool to view organization membership.
Get Organization DetailsTool to view the authenticated organization's details.
Get Sub-OrganizationsTool to view sub-organizations and their details.
Get ProfilesTool to list all profiles associated with the authenticated account.
Get Profile OptionsRetrieves all available configuration options for DNS profiles in Control D.
Get Profile by IDTool to retrieve details of a specific profile by its ID.
Get Profile AnalyticsRetrieve analytics data for a Control D profile.
Get Profile Analytics LogsRetrieves DNS query activity logs for a specific Control D profile.
Get Analytics Log EntryTool to retrieve a specific analytics log entry by its ID.
Get Profile Analytics SummaryTool to fetch a summary of analytics data for a given profile.
Get Profile Analytics Top DomainsTool to fetch top domains accessed within a specific profile.
Get Profile Top ServicesTool to fetch top services accessed within a profile.
Get Profile FiltersList all native (Control D curated) filters for a profile and their current states.
List External Filters for ProfileTool to list third-party filters for a specific profile.
Get Profile FoldersList all rule folders (groups) within a Control D profile.
List Custom DNS Rules for ProfileRetrieve custom DNS rules for a Control D profile.
Get Specific Rule in FolderTool to retrieve a specific rule within a folder by its ID.
Get Profile SchedulesTool to list schedules associated with a specific profile.
Get Profile ScheduleTool to retrieve a specific schedule by its ID within a profile.
Get Profile ServicesTool to list services associated with a specific profile.
Get ProxiesTool to retrieve the list of usable proxy locations that traffic can be redirected through.
Get Service CategoriesList all available service categories in Control D.
List Services by CategoryRetrieves all services within a specific ControlD service category.
Get UsersRetrieve the authenticated user's account information from Control D.
Create DeviceCreate a new device (DNS endpoint) in Control D.
Create ProfileCreate a new blank profile or clone an existing one.
Create Custom DNS RuleCreate custom DNS rules for a profile to control domain resolution.
Create Custom Rules in Profile FolderTool to create custom rules within a specific folder for a profile.
Create Profile ScheduleCreate a new time-based schedule within a Control D profile.
Modify DeviceModify an existing Control D device's settings.
Modify OrganizationModify organization settings such as name, contact details, website, and device limits.
Modify ProfileModify an existing profile by its ID.
Bulk Update Profile FiltersTool to bulk update filters on a specific profile.
Update External Filters for ProfileTool to update external filters for a specific profile.
Modify Profile FilterModify the enabled state of a specific native filter on a profile.
Modify Custom Rule for ProfileModify an existing custom DNS rule for a profile in Control D.
Update Custom Rule by Rule IDTool to update an existing custom rule by its ID.
Move Profile Rule to FolderTool to move a specific custom rule into a different folder.
Update Profile ScheduleTool to update a specific schedule within a profile.
Modify Service for ProfileTool to modify a specific service rule for a profile.

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

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Control d connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python

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.

Install dependencies

bash
pip install composio crewai crewai-tools[mcp] python-dotenv
What's happening:
  • composio connects your agent to Control d via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] includes MCP helpers
  • python-dotenv loads environment variables from .env

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
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 with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model

Import dependencies

python
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Control d MCP URL

Create a Composio Tool Router session for Control d

python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["control_d"])

url = session.mcp.url
What's happening:
  • You create a Control d only session through Composio
  • Composio returns an MCP HTTP URL that exposes Control d tools

Initialize the MCP Server

python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
What's Happening:
  • Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
  • MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
  • Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
  • Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
  • Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.

Create a CLI Chatloop and define the Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")

conversation_context = ""

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

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

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[agent], tasks=[task], verbose=False)
    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's Happening:
  • Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
  • Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
  • Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
  • Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
  • Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
  • Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.

Complete Code

Here's the complete code to get you started with Control d and CrewAI:

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["control_d"],
)
url = session.mcp.url

# Configure LLM
llm = LLM(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY"),
)

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

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

    conversation_context = ""

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

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

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

Conclusion

You now have a CrewAI agent connected to Control d through Composio's Tool Router. The agent can perform Control d operations through natural language commands.

Next steps:

  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations

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

FAQ

What are the differences in Tool Router MCP and Control d MCP?

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.

Can I use Tool Router MCP with CrewAI?

Yes, you can. CrewAI 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.

Can I manage the permissions and scopes for Control d while using Tool Router?

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.

How safe is my data with Composio Tool Router?

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.

Used by agents from

Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

Never worry about agent reliability

We handle tool reliability, observability, and security so you never have to second-guess an agent action.

Get started for freeGet a demo↗