# How to integrate Callpage MCP with Autogen

```json
{
  "title": "How to integrate Callpage MCP with Autogen",
  "toolkit": "Callpage",
  "toolkit_slug": "callpage",
  "framework": "AutoGen",
  "framework_slug": "autogen",
  "url": "https://composio.dev/toolkits/callpage/framework/autogen",
  "markdown_url": "https://composio.dev/toolkits/callpage/framework/autogen.md",
  "updated_at": "2026-05-12T10:04:54.488Z"
}
```

## Introduction

This guide walks you through connecting Callpage to AutoGen using the Composio tool router. By the end, you'll have a working Callpage agent that can list all widgets with enabled status, get sms statistics for widget 12345, create a custom voice message for spanish visitors through natural language commands.
This guide will help you understand how to give your AutoGen agent real control over a Callpage account through Composio's Callpage MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Callpage with

- [OpenAI Agents SDK](https://composio.dev/toolkits/callpage/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/callpage/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/callpage/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/callpage/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/callpage/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/callpage/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/callpage/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/callpage/framework/cli)
- [Google ADK](https://composio.dev/toolkits/callpage/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/callpage/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/callpage/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/callpage/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/callpage/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/callpage/framework/crew-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 Callpage
- Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
- Configure an Autogen AssistantAgent that can call Callpage tools
- Run a live chat loop where you ask the agent to perform Callpage 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 Callpage MCP server, and what's possible with it?

The Callpage MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Callpage account. It provides structured and secure access to your Callpage lead management tools, so your agent can perform actions like retrieving widgets, managing users, monitoring SMS activity, and customizing voice messages on your behalf.
- Retrieve and manage widgets: Quickly list all your Callpage widgets, access detailed widget configurations, and monitor widget status statistics to optimize lead capture.
- View and audit account users: Effortlessly fetch lists of all users and managers, including status summaries, to keep your team structure up to date and compliant.
- Monitor SMS and messaging activity: Access all SMS messages and gather statistics on SMS usage for specific widgets, helping you track engagement and campaign reach.
- Create custom voice messages: Enable your agent to generate personalized voice greetings for widgets, tailoring communication for both managers and visitors with ease.
- API connectivity and health checks: Let your agent verify API connectivity and status, ensuring seamless and reliable integration between Callpage and your workflows.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `CALLPAGE_ADD_USERS_TO_WIDGET` | Add Users to Widget | Tool to add users to a widget as managers. Use when you need to create or update manager assignments for a widget. If a user-widget pair already exists, the existing manager will be updated instead of creating a new one. |
| `CALLPAGE_CREATE_SMS_MESSAGE` | Create SMS Message | Tool to create custom SMS messages for specific widget events. Use when you need to set up automated SMS notifications for call events like completed dials, scheduled calls, or missed calls. |
| `CALLPAGE_CREATE_USER` | Create User | Tool to create a new user with specified name, phone number, email and role. Use when you need to add a new admin or manager user to your CallPage account. |
| `CALLPAGE_DELETE_MANAGER` | Delete Manager | Tool to delete a manager from a widget. Use when you need to remove a manager assignment after verifying both user_id and widget_id. |
| `CALLPAGE_DELETE_USER` | Delete User by Id | Tool to delete a user by id. Use when you need to remove an existing user after verifying their ID. |
| `CALLPAGE_GET_ALL_MANAGERS` | Get All Managers | Tool to retrieve a list of managers for a specific widget with pagination. Use when you need to page through all managers assigned to a widget after confirming its ID. |
| `CALLPAGE_GET_ALL_SMS_MESSAGES` | Get All SMS Messages | Tool to retrieve all SMS messages for a widget. Use when you need to fetch both default and custom SMS templates after confirming the widget exists. |
| `CALLPAGE_GET_ALL_USERS` | Get All Users | Tool to retrieve a list of all users with pagination. Use when you need to page through all users in your CallPage account to synchronize or audit user records. |
| `CALLPAGE_GET_ALL_VOICE_MESSAGES` | Get All Voice Messages | Tool to retrieve all voice messages for a widget. Returns custom voice messages if configured, otherwise returns default messages. Use when you need to view or audit voice message settings. |
| `CALLPAGE_GET_ALL_WIDGETS` | Get All Widgets | Tool to retrieve a list of widgets with pagination. Use when you need to page through all widgets after API authentication. |
| `CALLPAGE_GET_API_ROOT` | Get API Root | Tool to get the root API greeting. Use to verify connectivity and retrieve the initial API greeting after setting the API key. |
| `CALLPAGE_GET_CALLS_HISTORY` | Get Calls History | Tool to retrieve calls history with filtering and pagination. By default returns all calls for all users' widgets. Use when you need to query historical call data with optional filters for date range, status, widgets, users, tags, or phone numbers. |
| `CALLPAGE_GET_MANAGER` | Get Manager | Tool to retrieve a specific manager by user_id and widget_id. Use when you need detailed information about a manager's configuration, availability, and assigned departments. |
| `CALLPAGE_GET_MANAGER_STATUS_STATISTICS` | Get Manager Status Statistics | Tool to retrieve statistical data about manager statuses. Use when you need summary counts of enabled and disabled managers for a specific widget. |
| `CALLPAGE_GET_WIDGET` | Get Widget | Tool to retrieve details of a specific widget by id. Use when you have a widget id and need its complete configuration. |
| `CALLPAGE_POST_CREATE_MANAGER` | Create Manager | Tool to create a new manager for a widget. Use when you need to assign a user as a manager to handle calls for a specific widget. |
| `CALLPAGE_POST_CREATE_VOICE_MESSAGE` | Create Voice Message | Tool to create a custom voice message for a widget. Use when you need to customize greeting messages for manager or visitor after setting widget locale. |
| `CALLPAGE_POST_CREATE_WIDGET` | Create Widget | Tool to create a new widget. Use when you need to install a widget on your site and retrieve its ID. |
| `CALLPAGE_POST_DELETE_WIDGET` | Delete Widget by Id | Tool to delete a widget by id. Use when you need to remove an existing widget after verifying its ID. Example: Delete widget with id 3409. |
| `CALLPAGE_POST_RESET_SMS` | Reset SMS | Tool to reset SMS messages to default for a widget. Use when you need to restore default SMS templates after customization tests. |
| `CALLPAGE_POST_RESET_VOICE_MESSAGE` | Reset Voice Messages | Tool to reset voice messages to default for a widget. Use when you need to clear custom messages and revert to system defaults. Example: Reset all voice messages for widget with id 123. |
| `CALLPAGE_POST_UPDATE_MANAGER` | Update Manager | Tool to update an existing manager. Use when you need to modify a manager's availability or business hours after retrieving their record. |
| `CALLPAGE_POST_UPDATE_SMS` | Update SMS | Tool to update a custom SMS message for a widget. Use when you need to modify custom SMS templates. Note: it's impossible to update default SMS - if you haven't created custom SMS yet, use the create endpoint first. |
| `CALLPAGE_POST_UPDATE_USER` | Update User | Tool to update an existing user by ID. Use when you need to modify a user's details, phone number, role, or enabled status. This operation can override parent user depending on who makes the request. |
| `CALLPAGE_POST_UPDATE_WIDGET` | Update Widget | Tool to update an existing widget. Use when you need to change widget URL, description, settings, language, or enabled state. |
| `CALLPAGE_POST_WIDGET_CALL_OR_SCHEDULE` | Widget Call or Schedule | Tool to initiate or schedule a call via widget. Use when you need to call immediately or schedule at the first available timeslot through a widget. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Callpage MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Callpage. Instead of manually wiring Callpage APIs, OAuth, and scopes yourself, you get a structured, tool-based interface that an LLM can call safely.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

You will need:
- A Composio API key
- An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
- A Callpage account you can connect to Composio
- Some basic familiarity with Autogen and Python async

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

Install Composio, Autogen extensions, and dotenv.
What's happening:
- composio connects your agent to Callpage via MCP
- autogen-agentchat provides the AssistantAgent class
- autogen-ext-openai provides the OpenAI model client
- autogen-ext-tools provides MCP workbench support
```bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools
```

### 3. Set up environment variables

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 Callpage connections to use
```bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com
```

### 4. Import dependencies and create Tool Router session

What's happening:
- load_dotenv() reads your .env file
- Composio(api_key=...) initializes the SDK
- create(...) creates a Tool Router session that exposes Callpage tools
- session.mcp.url is the MCP endpoint that Autogen will connect to
```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 Callpage session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["callpage"]
    )
    url = session.mcp.url
```

### 5. Configure MCP parameters for Autogen

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
```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")}
)
```

### 6. Create the model client and agent

What's happening:
- OpenAIChatCompletionClient wraps the OpenAI model for Autogen
- McpWorkbench connects the agent to the MCP tools
- AssistantAgent is configured with the Callpage tools from the workbench
```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 Callpage assistant agent with MCP tools
    agent = AssistantAgent(
        name="callpage_assistant",
        description="An AI assistant that helps with Callpage operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )
```

### 7. Run the interactive chat loop

What's happening:
- The script prompts you in a loop with You:
- Autogen passes your input to the model, which decides which Callpage 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
```python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Callpage 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")
```

## Complete Code

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

## How to build Callpage MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/callpage/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/callpage/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/callpage/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/callpage/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/callpage/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/callpage/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/callpage/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/callpage/framework/cli)
- [Google ADK](https://composio.dev/toolkits/callpage/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/callpage/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/callpage/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/callpage/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/callpage/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/callpage/framework/crew-ai)

## Related Toolkits

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- [Botsonic](https://composio.dev/toolkits/botsonic) - Botsonic is a no-code AI chatbot builder for easily creating and deploying chatbots to your website. It empowers businesses to offer conversational experiences without writing code.
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- [Callingly](https://composio.dev/toolkits/callingly) - Callingly is a lead response management platform that automates immediate call and text follow-ups with new leads. It helps sales teams boost response speed and close more deals by connecting seamlessly with CRMs and lead sources.
- [Clearout](https://composio.dev/toolkits/clearout) - Clearout is an AI-powered service for verifying, finding, and enriching email addresses. It boosts deliverability and helps you discover high-quality leads effortlessly.
- [Clientary](https://composio.dev/toolkits/clientary) - Clientary is a platform for managing clients, invoices, projects, proposals, and more. It streamlines client work and saves you serious admin time.
- [Convolo ai](https://composio.dev/toolkits/convolo_ai) - Convolo ai is an AI-powered communications platform for sales teams. It accelerates lead response and improves conversion rates by automating calls and integrating workflows.
- [Delighted](https://composio.dev/toolkits/delighted) - Delighted is a customer feedback platform based on the Net Promoter System®. It helps you quickly gather, track, and act on customer sentiment.
- [Docsbot ai](https://composio.dev/toolkits/docsbot_ai) - Docsbot ai is a platform that lets you build custom AI chatbots trained on your documentation. It automates customer support and content generation, saving time and improving response quality.
- [Emelia](https://composio.dev/toolkits/emelia) - Emelia is an all-in-one B2B prospecting platform for cold-email, LinkedIn outreach, and prospect research. It streamlines outbound campaigns so you can find, engage, and warm up leads faster.
- [Findymail](https://composio.dev/toolkits/findymail) - Findymail is a B2B data provider offering verified email and phone contacts for sales prospecting. Enhance outreach with automated exports, email verification, and CRM enrichment.
- [Freshdesk](https://composio.dev/toolkits/freshdesk) - Freshdesk is customer support software with ticketing and automation tools. It helps teams streamline helpdesk operations for faster, better customer support.
- [Fullenrich](https://composio.dev/toolkits/fullenrich) - FullEnrich is a B2B contact enrichment platform that aggregates emails and phone numbers from 15+ data vendors. Instantly find and verify lead contact data to boost your outreach.
- [Gatherup](https://composio.dev/toolkits/gatherup) - GatherUp is a customer feedback and online review management platform. It helps businesses boost their reputation by streamlining how they collect and manage customer feedback.
- [Getprospect](https://composio.dev/toolkits/getprospect) - Getprospect is a business email discovery tool with LinkedIn integration. Use it to quickly find and verify professional email addresses.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Callpage MCP?

With a standalone Callpage MCP server, the agents and LLMs can only access a fixed set of Callpage tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Callpage and many other apps based on the task at hand, all through a single MCP endpoint.

### Can I use Tool Router MCP with Autogen?

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 Callpage tools.

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

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

---
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