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How to integrate Dialmycalls MCP with Autogen

Connect Autogen to Dialmycalls MCP. Add a new contact named lisa chen, create a group for emergency alerts, and more using natural language, with authentication handled for you.

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Dialmycalls is a mass notification service for sending voice and text messages to contacts. It helps teams and organizations quickly broadcast urgent alerts and updates.

25 Tools

Introduction

This guide walks you through connecting Dialmycalls to AutoGen using the Composio tool router. By the end, you'll have a working Dialmycalls agent that can add contacts and groups, list calls and text broadcasts, manage caller IDs, and review recordings through natural language commands.

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

Also integrate Dialmycalls with

Claude CodeClaude CoworkOpenAI Agents SDKClaude Agent SDKCodexOpenClawHermesAtomic AgentGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAIPydantic AI

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 Dialmycalls
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Dialmycalls tools
  • Run a live chat loop where you ask the agent to perform Dialmycalls 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 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.

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

Supported Tools

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

Add Access Account

Tool to add a new access (sub) account.

Add Contact

Tool to add a contact to your contact list.

Add Group

Tool to add a new contact group.

Delete Access Account

Tool to delete an access (sub) account by ID.

Delete Caller ID

Tool to delete a caller ID.

Delete Contact

Tool to delete a contact by ID.

Delete Group

Tool to delete a contact group by ID.

Delete Recording

Tool to delete a recording by ID.

Get Access Account

Tool to retrieve an access (sub) account by ID.

Get Account

Tool to retrieve your main account details.

Get Caller ID

Tool to retrieve a caller ID by ID.

Get Contact

Tool to retrieve a contact by its unique ID.

Get Group

Retrieve a contact group by ID to review its details, for example after creating or updating it.

Get Recording

Retrieve a recording by ID to review its details and recording file URL.

List Access Accounts

Tool to list all access (sub) accounts.

List Caller IDs

List caller IDs on the account.

List Calls

Tool to list all call broadcasts on the account.

List Contacts

Tool to list all contacts in your contact list.

List Do Not Contacts

List Do Not Contact entries for review.

List Groups

List contact groups to get an overview of existing groups before sending messages.

List Recordings

List account recordings for auditing or management, with optional page and limit parameters.

List Text Broadcasts

List outgoing text broadcasts for review, with optional date, status, limit, and offset parameters.

List Vanity Numbers

List vanity numbers on the account, with optional limit and offset parameters for pagination.

Update Access Account

Tool to update an existing access (sub) account by ID.

Update Caller ID

Tool to update an existing caller ID by ID.

FRAMEWORKS

How to build Dialmycalls MCP Agent with another framework

Claude Code logo

Claude Code

Use Dialmycalls MCP with Claude Code

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Claude Cowork

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OpenAI Agents SDK logo

OpenAI Agents SDK

Use Dialmycalls MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Dialmycalls MCP with Claude Agent SDK

Codex logo

Codex

Use Dialmycalls MCP with Codex

OpenClaw logo

OpenClaw

Use Dialmycalls MCP with OpenClaw

Hermes logo

Hermes

Use Dialmycalls MCP with Hermes

Atomic Agent logo

Atomic Agent

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Google ADK logo

Google ADK

Use Dialmycalls MCP with Google ADK

LangChain logo

LangChain

Use Dialmycalls MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Dialmycalls MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Dialmycalls MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Dialmycalls MCP with LlamaIndex

CrewAI logo

CrewAI

Use Dialmycalls MCP with CrewAI

Pydantic AI logo

Pydantic AI

Use Dialmycalls MCP with Pydantic AI

FAQ

Frequently asked questions

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