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How to integrate Supadata MCP with Autogen

Connect Autogen to Supadata MCP. Extract all urls from a competitor website, scrape the main content from a blog post, and more using natural language, with authentication handled for you.

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Supadata is a web and video-to-text API that extracts structured data from videos and websites. It enables fast, automated content parsing for AI training and analysis.

20 Tools

Introduction

This guide walks you through connecting Supadata to AutoGen using the Composio tool router. By the end, you'll have a working Supadata agent that can fetch YouTube transcripts, translate transcripts, scrape and crawl websites, search YouTube, and pull video and channel metadata through natural language commands.

This guide will help you understand how to give your AutoGen agent real control over a Supadata account through Composio's Supadata MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Supadata with

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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 Supadata
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Supadata tools
  • Run a live chat loop where you ask the agent to perform Supadata 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 Supadata MCP server, and what's possible with it?

The Supadata MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Supadata account. It provides structured and secure access to web and video data extraction tools, so your agent can perform actions like scraping websites, mapping URLs, transcribing YouTube videos, and gathering channel or playlist metadata on your behalf.

  • Comprehensive website scraping and content extraction: Instruct your agent to pull structured content from any website, enabling programmatic parsing and analysis for research or automation.
  • Automated sitemap and URL mapping: Let your agent retrieve all URLs from a given website, making it easy to analyze site structure or perform link audits.
  • YouTube video and channel metadata retrieval: Have your agent fetch detailed metadata for any YouTube video, playlist, or channel—including titles, descriptions, stats, and more.
  • YouTube search and discovery: Empower your agent to search YouTube for videos, channels, or playlists by keyword, streamlining content discovery and curation tasks.
  • Playlist and channel video extraction: Direct your agent to list and export videos from specific YouTube channels or playlists, complete with pagination support for large collections.

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

Supported Tools

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

Get Account Information

Retrieve organization details, plan information, and credit usage for the authenticated account.

Get Media Metadata

Retrieve unified metadata for supported social-media content.

Get Video Transcript

Get transcript from a video on supported platforms or from a file URL.

Get Transcript by Job ID

Get the status and results of an asynchronous transcript job by job ID.

Get Video Extraction Result

Retrieve the status and result of a video extraction job using your own Supadata connection.

Get Web Crawl Result

Poll a web crawl and retrieve its pages using your own Supadata connection.

Website URL Map

Crawl a website and extract all URLs/links found on it.

Scrape Web Page

Extract content from any webpage and convert it to Markdown format.

Get YouTube Batch Result

Poll a YouTube transcript or video metadata batch using your own Supadata connection.

Get YouTube Channel Metadata

Fetches metadata for a YouTube channel including name, description, subscriber count, video count, view count, and channel images.

Get YouTube Channel Videos

Tool to retrieve video IDs from a YouTube channel.

Get YouTube Playlist Metadata

Retrieve metadata for a YouTube playlist including title, description, video count, view count, last updated timestamp, and channel information.

Get YouTube Playlist Videos

Tool to retrieve video IDs from a YouTube playlist.

Get YouTube Video Metadata

Retrieve comprehensive metadata for a YouTube video by its ID.

Search YouTube

Search YouTube for videos, channels, or playlists by keyword.

Start Video Extraction

Start asynchronous structured extraction from public videos on supported social platforms or public media files, using a prompt, schema, or both.

Start Web Crawl

Start an asynchronous website crawl following child links under the supplied URL.

Start YouTube Transcript Batch

Start an asynchronous YouTube transcript batch from exactly one list of video IDs, playlist, or channel.

Start YouTube Video Metadata Batch

Start an asynchronous YouTube video metadata batch from exactly one list of video IDs, playlist, or channel.

Translate YouTube Transcript

Translate a YouTube transcript into a requested ISO 639-1 language.

FRAMEWORKS

How to build Supadata MCP Agent with another framework

Claude Code logo

Claude Code

Use Supadata MCP with Claude Code

Cursor logo

Cursor

Use Supadata MCP with Cursor

ChatGPT logo

ChatGPT

Use Supadata MCP with ChatGPT

Claude Cowork logo

Claude Cowork

Use Supadata MCP with Claude Cowork

Antigravity logo

Antigravity

Use Supadata MCP with Antigravity

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Supadata MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Supadata MCP with Claude Agent SDK

Codex logo

Codex

Use Supadata MCP with Codex

Grok Build logo

Grok Build

Use Supadata MCP with Grok Build

VS Code logo

VS Code

Use Supadata MCP with VS Code

OpenCode logo

OpenCode

Use Supadata MCP with OpenCode

OpenClaw logo

OpenClaw

Use Supadata MCP with OpenClaw

Hermes logo

Hermes

Use Supadata MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Supadata MCP with Atomic Agent

Pi logo

Pi

Use Supadata MCP with Pi

DeepSeek Harness logo

DeepSeek Harness

Use Supadata MCP with DeepSeek Harness

Google ADK logo

Google ADK

Use Supadata MCP with Google ADK

LangChain logo

LangChain

Use Supadata MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Supadata MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Supadata MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Supadata MCP with LlamaIndex

CrewAI logo

CrewAI

Use Supadata MCP with CrewAI

Pydantic AI logo

Pydantic AI

Use Supadata MCP with Pydantic AI

FAQ

Frequently asked questions

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

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 Supadata tools.

Yes, absolutely. You can configure which Supadata 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.

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 Supadata data and credentials are handled as safely as possible.

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