How to integrate Dialmycalls MCP with LangChain

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Introduction

This guide walks you through connecting Dialmycalls to LangChain using the Composio tool router. By the end, you'll have a working Dialmycalls agent that can add a new contact named lisa chen, create a group for emergency alerts, delete the caller id ending in 4321, get my account's remaining message credits through natural language commands.

This guide will help you understand how to give your LangChain agent real control over a Dialmycalls account through Composio's Dialmycalls 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 Dialmycalls project to Composio
  • Create a Tool Router MCP session for Dialmycalls
  • Initialize an MCP client and retrieve Dialmycalls tools
  • Build a LangChain agent that can interact with Dialmycalls
  • 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 Dialmycalls MCP server, and what's possible with it?

The Dialmycalls MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Dialmycalls account. It provides structured and secure access to your mass notification system, allowing your agent to manage contacts, groups, and broadcast voice or text messages—all on your behalf.

  • Contact and group management: Effortlessly add, update, or remove individual contacts and organize recipients into groups for targeted messaging.
  • Account and sub-account administration: View your main account details, manage access (sub) accounts, and streamline team communication permissions.
  • Broadcast preparation: Set up caller IDs, upload or delete recordings, and get everything ready for your next mass notification campaign.
  • Data cleanup and maintenance: Easily delete old contacts, groups, caller IDs, or recordings to keep your Dialmycalls account organized and up to date.

Supported Tools & Triggers

Tools
Add Access AccountTool to add a new access (sub) account.
Add ContactTool to add a contact to your contact list.
Add GroupTool to add a new contact group.
Delete Access AccountTool to delete an access (sub) account by id.
Delete Caller IDTool to delete a caller id.
Delete ContactTool to delete a contact by id.
Delete GroupTool to delete a contact group by id.
Delete RecordingTool to delete a recording by id.
Get Access AccountTool to retrieve an access (sub) account by id.
Get AccountTool to retrieve your main account details.
Get Caller IDTool to retrieve a caller id by id.
Get ContactTool to retrieve a contact by its unique id.
Get GroupTool to retrieve a contact group by id.
Get RecordingTool to retrieve a recording by id.
List Access AccountsTool to list all access (sub) accounts.
List Caller IDsTool to list all caller ids on the account.
List CallsTool to list all call broadcasts on the account.
List ContactsTool to list all contacts in your contact list.
List Contacts in GroupTool to list contacts by contact group id.
List Do Not ContactsTool to list all do not contact entries.
List GroupsTool to list all contact groups.
List RecordingsTool to list all recordings.
List Text BroadcastsTool to list all outgoing text broadcasts.
List Vanity NumbersTool to list all vanity numbers.
Update Access AccountTool to update an existing access (sub) account by id.
Update Caller IDTool to update an existing caller id by id.

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 Dialmycalls 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 Dialmycalls tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

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

url = session.mcp.url
What's happening:
  • We're creating a Tool Router session that gives your agent access to Dialmycalls 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 Dialmycalls tools as needed

Configure the agent with the MCP URL

client = MultiServerMCPClient({
    "dialmycalls-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 Dialmycalls MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • get_tools() retrieves all available Dialmycalls 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 Dialmycalls 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 Dialmycalls 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=['dialmycalls']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "dialmycalls-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 Dialmycalls 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 Dialmycalls 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 Dialmycalls MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Dialmycalls MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Dialmycalls MCP with Claude Agent SDK

Google ADK

Google ADK

Use Dialmycalls MCP with Google ADK

Vercel AI SDK

Vercel AI SDK

Use Dialmycalls MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Dialmycalls MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Dialmycalls MCP with LlamaIndex

CrewAI

CrewAI

Use Dialmycalls MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Dialmycalls MCP?

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

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

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

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