# How to integrate Supadata MCP with Autogen ```json { "title": "How to integrate Supadata MCP with Autogen", "toolkit": "Supadata", "toolkit_slug": "supadata", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/supadata/framework/autogen", "markdown_url": "https://composio.dev/toolkits/supadata/framework/autogen.md", "updated_at": "2026-05-12T10:27:29.162Z" } ``` ## 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 extract all urls from a competitor website, scrape the main content from a blog post, list videos uploaded by a youtube channel 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 - [ChatGPT](https://composio.dev/toolkits/supadata/framework/chatgpt) - [OpenAI Agents SDK](https://composio.dev/toolkits/supadata/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/supadata/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/supadata/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/supadata/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/supadata/framework/codex) - [Cursor](https://composio.dev/toolkits/supadata/framework/cursor) - [VS Code](https://composio.dev/toolkits/supadata/framework/vscode) - [OpenCode](https://composio.dev/toolkits/supadata/framework/opencode) - [OpenClaw](https://composio.dev/toolkits/supadata/framework/openclaw) - [Hermes](https://composio.dev/toolkits/supadata/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/supadata/framework/cli) - [Google ADK](https://composio.dev/toolkits/supadata/framework/google-adk) - [LangChain](https://composio.dev/toolkits/supadata/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/supadata/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/supadata/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/supadata/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/supadata/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 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. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `SUPADATA_GET_ME` | Get Account Information | Retrieve organization details, plan information, and credit usage for the authenticated account. Use this to check account status, credit balance, and subscription plan. | | `SUPADATA_GET_TRANSCRIPT` | Get Video Transcript | Get transcript from a video on supported platforms or from a file URL. Use this tool when you need to: - Retrieve transcripts from YouTube, TikTok, Twitter, Instagram, or Facebook videos - Extract transcript from video file URLs - Get transcripts in specific languages - Choose between native captions or AI-generated transcripts For large videos, the API returns a job ID. You'll need to poll the /transcript/{jobId} endpoint to get the final result. For smaller videos, the transcript is returned immediately. The response varies based on the 'text' parameter: - text=true: Returns plain text transcript as a string - text=false: Returns structured list of chunks with timestamps and text | | `SUPADATA_GET_TRANSCRIPT_BY_JOB_ID` | Get Transcript by Job ID | Get results for a transcript job by job ID. Use this to retrieve results of asynchronous transcript processing. Check the status field to determine if the job is complete. | | `SUPADATA_GET_WEB_MAP` | Website URL Map | Crawl a website and extract all URLs/links found on it. Use this to create a sitemap, discover all pages of a website, or prepare for content scraping across multiple pages. Returns a list of all URLs discovered during the crawl. | | `SUPADATA_GET_WEB_SCRAPE` | Scrape Web Page | Extract content from any webpage and convert it to Markdown format. Use this tool when you need to: - Read and extract text content from a web page - Get metadata (title, description) from a webpage - Discover links on a webpage - Get character counts of page content The tool returns the page content in Markdown format, making it easy to process and understand. One API credit is consumed per scrape request. | | `SUPADATA_GET_YOUTUBE_CHANNEL` | Get YouTube Channel Metadata | Fetches metadata for a YouTube channel including name, description, subscriber count, video count, view count, and channel images. Accepts channel IDs, handles, or full YouTube URLs. | | `SUPADATA_GET_YOUTUBE_CHANNEL_VIDEOS` | Get YouTube Channel Videos | Tool to retrieve video IDs from a YouTube channel. Returns lists of regular video IDs, YouTube Shorts IDs, and live stream IDs. Videos are ordered latest first. Use this to get video IDs that can be passed to the Get YouTube Video endpoint for full metadata. | | `SUPADATA_GET_YOUTUBE_PLAYLIST` | Get YouTube Playlist Metadata | Retrieve metadata for a YouTube playlist including title, description, video count, view count, last updated timestamp, and channel information. Use this when you need playlist-level information. For the list of videos in a playlist, use the Get YouTube Playlist Videos action instead. | | `SUPADATA_GET_YOUTUBE_PLAYLIST_VIDEOS` | Get YouTube Playlist Videos | Tool to retrieve video IDs from a YouTube playlist. Returns lists of standard video IDs, YouTube Shorts IDs, and live stream IDs contained in the playlist. | | `SUPADATA_GET_YOUTUBE_VIDEO` | Get YouTube Video Metadata | Retrieve comprehensive metadata for a YouTube video by its ID. Use this tool when you need to get details about a specific YouTube video including: - Title, description, and tags - Channel information - View and like counts - Upload date and duration - Live stream status - Available transcript languages The video_id is the 11-character identifier found in YouTube URLs (e.g., 'dQw4w9WgXcQ' from 'https://youtube.com/watch?v=dQw4w9WgXcQ'). | | `SUPADATA_SEARCH_YOUTUBE` | Search YouTube | Search YouTube for videos, channels, or playlists by keyword. Returns matching content with metadata like titles, thumbnails, view counts, and channel information. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Supadata MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Supadata. Instead of manually wiring Supadata 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 Supadata 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 Supadata 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 Supadata 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 Supadata 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 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 ``` ### 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 Supadata 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 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 ) ``` ### 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 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 ```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") ``` ## 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 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. ## How to build Supadata MCP Agent with another framework - [ChatGPT](https://composio.dev/toolkits/supadata/framework/chatgpt) - [OpenAI Agents SDK](https://composio.dev/toolkits/supadata/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/supadata/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/supadata/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/supadata/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/supadata/framework/codex) - [Cursor](https://composio.dev/toolkits/supadata/framework/cursor) - [VS Code](https://composio.dev/toolkits/supadata/framework/vscode) - [OpenCode](https://composio.dev/toolkits/supadata/framework/opencode) - [OpenClaw](https://composio.dev/toolkits/supadata/framework/openclaw) - [Hermes](https://composio.dev/toolkits/supadata/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/supadata/framework/cli) - [Google ADK](https://composio.dev/toolkits/supadata/framework/google-adk) - [LangChain](https://composio.dev/toolkits/supadata/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/supadata/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/supadata/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/supadata/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/supadata/framework/crew-ai) ## Related Toolkits - [Excel](https://composio.dev/toolkits/excel) - Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. It's the go-to tool for calculations, reporting, and flexible data management. - [21risk](https://composio.dev/toolkits/_21risk) - 21RISK is a web app built for easy checklist, audit, and compliance management. It streamlines risk processes so teams can focus on what matters. - [Abstract](https://composio.dev/toolkits/abstract) - Abstract provides a suite of APIs for automating data validation and enrichment tasks. It helps developers streamline workflows and ensure data quality with minimal effort. - [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time. - [Agenty](https://composio.dev/toolkits/agenty) - Agenty is a web scraping and automation platform for extracting data and automating browser tasks—no coding needed. It streamlines data collection, monitoring, and repetitive online actions. - [Ambee](https://composio.dev/toolkits/ambee) - Ambee is an environmental data platform providing real-time, hyperlocal APIs for air quality, weather, and pollen. Get precise environmental insights to power smarter decisions in your apps and workflows. - [Ambient weather](https://composio.dev/toolkits/ambient_weather) - Ambient Weather is a platform for personal weather stations with a robust API for accessing local, real-time, and historical weather data. Get detailed environmental insights directly from your own sensors for smarter apps and automations. - [Anonyflow](https://composio.dev/toolkits/anonyflow) - Anonyflow is a service for encryption-based data anonymization and secure data sharing. It helps organizations meet GDPR, CCPA, and HIPAA data privacy compliance requirements. - [Api ninjas](https://composio.dev/toolkits/api_ninjas) - Api ninjas offers 120+ public APIs spanning categories like weather, finance, sports, and more. Developers use it to supercharge apps with real-time data and actionable endpoints. - [Api sports](https://composio.dev/toolkits/api_sports) - Api sports is a comprehensive sports data platform covering 2,000+ competitions with live scores and 15+ years of stats. Instantly access up-to-date sports information for analysis, apps, or chatbots. - [Apify](https://composio.dev/toolkits/apify) - Apify is a cloud platform for building, deploying, and managing web scraping and automation tools called Actors. It lets you automate data extraction and workflow tasks at scale—no infrastructure headaches. - [Autom](https://composio.dev/toolkits/autom) - Autom is a lightning-fast search engine results data platform for Google, Bing, and Brave. Developers use it to access fresh, low-latency SERP data on demand. - [Beaconchain](https://composio.dev/toolkits/beaconchain) - Beaconchain is a real-time analytics platform for Ethereum 2.0's Beacon Chain. It provides detailed insights into validators, blocks, and overall network performance. - [Big data cloud](https://composio.dev/toolkits/big_data_cloud) - BigDataCloud provides APIs for geolocation, reverse geocoding, and address validation. Instantly access reliable location intelligence to enhance your applications and workflows. - [Bigpicture io](https://composio.dev/toolkits/bigpicture_io) - BigPicture.io offers APIs for accessing detailed company and profile data. Instantly enrich your applications with up-to-date insights on 20M+ businesses. - [Bitquery](https://composio.dev/toolkits/bitquery) - Bitquery is a blockchain data platform offering indexed, real-time, and historical data from 40+ blockchains via GraphQL APIs. Get unified, reliable access to complex on-chain data for analytics, trading, and research. - [Brightdata](https://composio.dev/toolkits/brightdata) - Brightdata is a leading web data platform offering advanced scraping, SERP APIs, and anti-bot tools. It lets you collect public web data at scale, bypassing blocks and friction. - [Builtwith](https://composio.dev/toolkits/builtwith) - BuiltWith is a web technology profiler that uncovers the technologies powering any website. Gain actionable insights into analytics, hosting, and content management stacks for smarter research and lead generation. - [Byteforms](https://composio.dev/toolkits/byteforms) - Byteforms is an all-in-one platform for creating forms, managing submissions, and integrating data. It streamlines workflows by centralizing form data collection and automation. - [Cabinpanda](https://composio.dev/toolkits/cabinpanda) - Cabinpanda is a data collection platform for building and managing online forms. It helps streamline how you gather, organize, and analyze responses. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Supadata MCP? 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. ### 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 Supadata tools. ### Can I manage the permissions and scopes for Supadata while using Tool Router? 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. ### 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 Supadata data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)