How to integrate Control d MCP with LangChain

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Introduction

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

This guide will help you understand how to give your LangChain 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.

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Control d project to Composio
  • Create a Tool Router MCP session for Control d
  • Initialize an MCP client and retrieve Control d tools
  • Build a LangChain agent that can interact with Control d
  • Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

  • Agent Framework: Build agents that can use tools and make decisions
  • MCP Integration: Connect to external services through Model Context Protocol adapters
  • Memory Management: Maintain conversation history across interactions
  • Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

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 IDTool to delete a Control-D device.
Delete Profile by IDTool to delete a profile.
Delete Profile Rule by HostnameTool to delete a specific custom rule by hostname from a profile.
Delete Profile Rule by Rule IDTool to delete a specific custom rule by its ID within a profile.
Delete Profile Rule in FolderTool to delete a specific custom rule within a folder.
Delete Profile ScheduleTool to delete a specific schedule within a profile.
List Known Access IPsTool to list known IPs associated with the account.
Get Analytics EndpointsTool to list analytics storage regions and their endpoints.
Get DevicesTool to list all devices associated with the account.
Get Organization DetailsTool to view the authenticated organization's details.
Get ProfilesTool to list all profiles associated with the authenticated account.
Get Profile OptionsTool to get all available profile options.
Get Profile by IDTool to retrieve details of a specific profile by its ID.
Get Profile AnalyticsTool to retrieve analytics data for a specific profile.
Get Profile Analytics LogsTool to list analytics log entries for a given 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 FiltersTool to list native filters associated with a specific profile.
List External Filters for ProfileTool to list third-party filters for a specific profile.
Get Profile FoldersTool to list rule folders (groups) within a profile.
List Custom Rules for ProfileTool to retrieve custom rules associated with a specific profile.
List Custom Rules in FolderTool to retrieve custom rules in a specific folder of a profile.
Get Custom Rule by Rule IDTool to retrieve details of a specific custom rule by its ID.
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 Service CategoriesTool to list all service categories.
List Services by CategoryTool to list all services within a specific category.
Get UsersTool to retrieve user account data.
Create DeviceTool to create a new device.
Create ProfileTool to create a new blank profile or clone an existing one.
Create Custom Rules for ProfileTool to create custom rules for a profile.
Create Custom Rules in Profile FolderTool to create custom rules within a specific folder for a profile.
Create Profile ScheduleTool to create a new schedule within a specific profile.
Modify DeviceTool to modify an existing device.
Modify OrganizationTool to modify organization settings and limits.
Update Profile by IDTool to modify an existing profile by 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 FilterTool to modify the enabled state of a specific filter on a profile.
Modify Custom Rules for ProfileTool to modify existing custom rule(s) for a profile.
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 Tool Router?

Composio's Tool Router 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 Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router 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 this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI API key
  • Basic familiarity with Python and async programming

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

pip install composio-langchain langchain-mcp-adapters langchain python-dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • composio-langchain provides Composio integration for LangChain
  • langchain-mcp-adapters enables MCP client connections
  • langchain is the core agent framework
  • python-dotenv loads environment variables

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_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's API
  • COMPOSIO_USER_ID identifies the user for session management
  • OPENAI_API_KEY enables access to OpenAI's language models

Import dependencies

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Control d functionality through MCP

Initialize Composio client

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
  • Creating a Composio instance that will manage our connection to Control d tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

# Create Tool Router session for Control d
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['control_d']
)

url = session.mcp.url
What's happening:
  • We're creating a Tool Router session that gives your agent access to Control d tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
  • This approach allows the agent to dynamically load and use Control d tools as needed

Configure the agent with the MCP URL

client = MultiServerMCPClient({
    "control_d-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Control d MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • get_tools() retrieves all available Control d tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model

Set up interactive chat interface

conversation_history = []

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")

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

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

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
What's happening:
  • We initialize an empty conversation_history list to maintain context across interactions
  • A while loop continuously accepts user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the ainvoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully

Run the application

if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • We call the main() function using asyncio.run() to start the application

Complete Code

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

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['control_d']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "control_d-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    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")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

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

Conclusion

You've successfully built a LangChain agent that can interact with Control d through Composio's Tool Router.

Key features of this implementation:

  • Dynamic tool loading through Composio's Tool Router
  • Conversation history maintenance for context-aware responses
  • Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

How to build Control d MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Control d MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Control d MCP with Claude Agent SDK

Google ADK

Google ADK

Use Control d MCP with Google ADK

Vercel AI SDK

Vercel AI SDK

Use Control d MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Control d MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Control d MCP with LlamaIndex

CrewAI

CrewAI

Use Control d MCP with CrewAI

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 LangChain?

Yes, you can. LangChain 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.

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