# How to integrate Data247 MCP with Autogen

```json
{
  "title": "How to integrate Data247 MCP with Autogen",
  "toolkit": "Data247",
  "toolkit_slug": "data247",
  "framework": "AutoGen",
  "framework_slug": "autogen",
  "url": "https://composio.dev/toolkits/data247/framework/autogen",
  "markdown_url": "https://composio.dev/toolkits/data247/framework/autogen.md",
  "updated_at": "2026-03-29T06:29:36.841Z"
}
```

## Introduction

This guide walks you through connecting Data247 to AutoGen using the Composio tool router. By the end, you'll have a working Data247 agent that can validate an email address for accuracy, find carrier for a phone number, enrich contact record with address details through natural language commands.
This guide will help you understand how to give your AutoGen agent real control over a Data247 account through Composio's Data247 MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Data247 with

- [OpenAI Agents SDK](https://composio.dev/toolkits/data247/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/data247/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/data247/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/data247/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/data247/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/data247/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/data247/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/data247/framework/cli)
- [Google ADK](https://composio.dev/toolkits/data247/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/data247/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/data247/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/data247/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/data247/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/data247/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 Data247
- Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
- Configure an Autogen AssistantAgent that can call Data247 tools
- Run a live chat loop where you ask the agent to perform Data247 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 Data247 MCP server, and what's possible with it?

The Data247 MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Data247 account. It provides structured and secure access so your agent can perform Data247 operations on your behalf.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `DATA247_APPEND_EMAIL` | Append Email by Name and Address | Tool to find email addresses associated with name and postal address. Use when you need to discover the email address for a contact given their name and residential or business address. |
| `DATA247_APPEND_GENDER` | Append Gender by First Name | Tool to determine a person's probable gender based on their first (given) name. Use when you need to infer gender from a first name with confidence percentage. |
| `DATA247_APPEND_NAME` | Append Name (CNAM Lookup) | Tool to get CNAM (Caller Name Delivery) data for a phone number. Use when you need to find the registered owner name associated with a phone number from carrier-grade telco data. |
| `DATA247_APPEND_PHONE` | Append Phone to Contact | Tool to append phone numbers to contact records using name and address. Use when you need to find phone numbers (business or residential) associated with a person's name and address. Returns primary phone with type classification and additional phone numbers if available. |
| `DATA247_APPEND_PROPERTY_DATA` | Append Property Data | Tool to retrieve comprehensive property data including home stats, ownership information, financials and foreclosure data. Use when you need detailed property information for any US address. |
| `DATA247_APPEND_REVERSE_EMAIL_LOOKUP` | Append Reverse Email Lookup | Tool to perform reverse email lookup and retrieve contact information. Use when you need to find the name, phone, and address associated with an email address. Returns personal identifiers, contact details, and address components. |
| `DATA247_APPEND_REVERSE_PHONE_LOOKUP` | Append Reverse Phone Lookup | Tool to perform reverse phone lookup and retrieve name and address information. Use when you need to find the contact details associated with a phone number. Returns personal identifiers, address components, and demographic data. |
| `DATA247_APPEND_REVERSE_ZIPCODE_LOOKUP` | Append Reverse Zipcode Lookup | Tool to get formatted address components from a zipcode. Use when you need to retrieve city, state, county, congressional district, timezone, and other location data for a given 5 or 9 digit zipcode. |
| `DATA247_APPEND_ZIP_4_TO_ADDRESS` | Append ZIP+4 to Address | Tool to append ZIP+4 postal codes to addresses and standardize address information. Use when you need to obtain complete 9-digit zipcodes for accurate mail delivery or address validation. |
| `DATA247_CHECK_ACCOUNT_BALANCE` | Check Account Balance | Tool to check Data247 account balance and remaining credits. Use when you need to verify available credits before making API requests. |
| `DATA247_GET_CARRIER_TYPE_FOR_PHONE_NUMBER` | Get Carrier Type for Phone Number | Tool to determine carrier type for USA and Canadian phone numbers. Use when you need to identify if a phone number is a Mobile, Landline, or VOIP line. Returns the carrier type classification for the queried phone number. |
| `DATA247_GET_USA_CARRIER_AND_SMS_MMS_GATEWAY_INFO` | Get USA Carrier and SMS/MMS Gateway Info | Tool to get carrier information, wireless status, and SMS/MMS gateway addresses for USA phone numbers. Use when you need to obtain carrier name, determine if a number is wireless, or retrieve email-to-SMS and email-to-MMS gateway addresses for sending messages to a phone number. |
| `DATA247_CHECK_PHONE_NUMBER_FOR_FRAUD_SPAM` | Check Phone Number for Fraud/SPAM | Tool to check if a phone number is on SPAM callers list. Use when you need to verify if a phone number has been reported as spam or fraud. Returns spam risk level (Low, Medium, or High) and reason for the classification. |
| `DATA247_ADD_PHONE_TO_DO_NOT_CALL_LIST` | Add Phone to Do-Not-Call List | Tool to add phone numbers to your internal do-not-call (DNC) list. Use when you need to mark phone numbers that should not be contacted. Returns confirmation with action status 'ADDED' for successfully added numbers. |
| `DATA247_CHECK_PHONE_NUMBER_AGAINST_DNC_LISTS` | Check Phone Number Against DNC Lists | Tool to check if a phone number exists in Federal or internal Do-Not-Call list. Use when you need to verify if a phone number is safe to dial or if it's on a DNC list. Returns status indicating whether phone is OK-TO-DIAL, FEDERAL DNC, INTERNAL DNC, or UNAUTHORIZED. |
| `DATA247_REMOVE_PHONE_FROM_DO_NOT_CALL_LIST` | Remove Phone from Do-Not-Call List | Tool to remove phone numbers from your internal do-not-call (DNC) list. Use when you need to unmark phone numbers that were previously marked as do-not-call. Returns confirmation with action status 'REMOVED' for successfully removed numbers. |
| `DATA247_LOCATE_IP_ADDRESS_GET_GEOLOCATION_DATA` | Locate IP Address - Get Geolocation Data | Tool to get geolocation data for IPv4 addresses including city, state, country, and coordinates. Use when you need to determine the geographic location of an IP address worldwide. |
| `DATA247_GET_CARRIER_AND_GATEWAY_INFO_TEXT_SERVICE` | Get Carrier and Gateway Info (Text@ Service) | Tool to get carrier information, wireless status, and email-to-SMS/MMS gateway addresses for USA and Canadian phone numbers using the Text@ service. Use when you need to obtain carrier name, determine if a number is wireless, or retrieve email gateway addresses for sending SMS/MMS messages to a phone number. |
| `DATA247_VERIFY_USER_IDENTITY_TRUST_SCORE` | Verify User Identity Trust Score | Tool to verify user signup legitimacy and detect account creation fraud. Use when you need to check if a new user signup is from a legitimate user or a fraud attempt. Returns a trust score (1-100) and match statistics from cross-referencing user data with Data247's resources. Higher scores indicate legitimate signups; lower scores suggest potential fraud. Providing more user data parameters enables better fraud detection accuracy. |
| `DATA247_VERIFY_EMAIL_ADDRESS` | Verify Email Address | Tool to verify email address format and mailbox existence. Use when you need to validate that an email address is properly formatted and has a working mailbox. Also identifies free accounts and disposable email addresses. |
| `DATA247_VERIFY_PHONE_NUMBER_ACTIVE_STATUS` | Verify Phone Number Active Status | Tool to verify if a phone number is in-service and accepts inbound calls. Use when you need to validate phone number active status with confidence level. Returns whether the phone is active (YES/NO) and verification confidence (HIGH/LOW). Available in 100+ countries excluding USA/Canada. |
| `DATA247_VERIFY_USA_POSTAL_ADDRESS` | Verify USA Postal Address | Tool to verify and correct USA postal addresses to USPS standards. Use when you need to validate an address and get corrected components including street, city, state, ZIP, and detailed location data. Returns whether the address is valid and provides USPS-standardized address components. |

## Supported Triggers

None listed.

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

The Data247 MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Data247. Instead of manually wiring Data247 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 Data247 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 Data247 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 Data247 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 Data247 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 Data247 session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["data247"]
    )
    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 Data247 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 Data247 assistant agent with MCP tools
    agent = AssistantAgent(
        name="data247_assistant",
        description="An AI assistant that helps with Data247 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 Data247 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 Data247 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 Data247 session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["data247"]
    )
    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 Data247 assistant agent with MCP tools
        agent = AssistantAgent(
            name="data247_assistant",
            description="An AI assistant that helps with Data247 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 Data247 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 Data247 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 Data247, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

## How to build Data247 MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/data247/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/data247/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/data247/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/data247/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/data247/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/data247/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/data247/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/data247/framework/cli)
- [Google ADK](https://composio.dev/toolkits/data247/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/data247/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/data247/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/data247/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/data247/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/data247/framework/crew-ai)

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## Frequently Asked Questions

### What are the differences in Tool Router MCP and Data247 MCP?

With a standalone Data247 MCP server, the agents and LLMs can only access a fixed set of Data247 tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Data247 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 Data247 tools.

### Can I manage the permissions and scopes for Data247 while using Tool Router?

Yes, absolutely. You can configure which Data247 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 Data247 data and credentials are handled as safely as possible.

---
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