# How to integrate Bigpicture io MCP with Autogen ```json { "title": "How to integrate Bigpicture io MCP with Autogen", "toolkit": "Bigpicture io", "toolkit_slug": "bigpicture_io", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/bigpicture_io/framework/autogen", "markdown_url": "https://composio.dev/toolkits/bigpicture_io/framework/autogen.md", "updated_at": "2026-05-12T10:03:06.908Z" } ``` ## Introduction This guide walks you through connecting Bigpicture io to AutoGen using the Composio tool router. By the end, you'll have a working Bigpicture io agent that can find company details for apple.com, identify companies using this ip address, suggest domains for 'acme corporation' through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Bigpicture io account through Composio's Bigpicture io MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Bigpicture io with - [OpenAI Agents SDK](https://composio.dev/toolkits/bigpicture_io/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/bigpicture_io/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/bigpicture_io/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/bigpicture_io/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/bigpicture_io/framework/codex) - [OpenClaw](https://composio.dev/toolkits/bigpicture_io/framework/openclaw) - [Hermes](https://composio.dev/toolkits/bigpicture_io/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/bigpicture_io/framework/cli) - [Google ADK](https://composio.dev/toolkits/bigpicture_io/framework/google-adk) - [LangChain](https://composio.dev/toolkits/bigpicture_io/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/bigpicture_io/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/bigpicture_io/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/bigpicture_io/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/bigpicture_io/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 Bigpicture io - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Bigpicture io tools - Run a live chat loop where you ask the agent to perform Bigpicture io 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 Bigpicture io MCP server, and what's possible with it? The Bigpicture io MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Bigpicture io account. It provides structured and secure access to comprehensive company and domain data, so your agent can perform actions like finding company profiles, mapping company names to domains, and discovering company info from IP addresses—all on your behalf. - Company domain lookup by name: Instantly find up to three likely company domains when you provide a business name, making it easy to identify and validate organizations. - Detailed company profile by website domain: Retrieve rich and up-to-date company information by specifying a company's website domain, perfect for enrichment or qualification workflows. - IP address to company matching: Uncover the company behind any IP address, helping with cybersecurity, analytics, or lead identification tasks. - Data enrichment for sales and marketing: Supercharge your prospecting and market research by letting your agent fetch background details for millions of businesses. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `BIGPICTURE_IO_COMPANY_FIND` | Company Find | Tool to lookup company data by domain name. Use when you need detailed company profile by providing a website domain. Use after confirming domain correctness. | | `BIGPICTURE_IO_FIND_COMPANY_STREAM` | Find Company Stream | Tool to lookup company data by domain with streaming response. Holds connection open until data is ready, avoiding 202 async responses. Use when you need immediate company data without async polling. Rate limited to 5 requests per minute. | | `BIGPICTURE_IO_IP_TO_COMPANY` | IP to Company Lookup | Lookup company information by IP address using BigPicture's IP-to-Company API. Returns detailed company data including: - Company name, domain, description, and legal name - Geographic location of the IP (city, state, country, coordinates) - Confidence score indicating match reliability (0.0-1.0) - Network ownership type: 'business' (company-owned), 'isp' (ISP), or 'hosting' (cloud provider) - Company metrics (employees, revenue, market cap) - Industry categorization - WHOIS and ASN registration data Use this tool when you need to identify which company owns or operates from a given IP address. Works with both IPv4 and IPv6 addresses. | | `BIGPICTURE_IO_NAME_TO_DOMAIN_SEARCH` | Name to Domain Search | Tool to find company domain(s) by company name. Use when you have a company name and need up to 3 likely domains. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Bigpicture io MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Bigpicture io. Instead of manually wiring Bigpicture io 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 Bigpicture io 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 Bigpicture io 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 Bigpicture io 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 Bigpicture io 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 Bigpicture io session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["bigpicture_io"] ) 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 Bigpicture io 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 Bigpicture io assistant agent with MCP tools agent = AssistantAgent( name="bigpicture_io_assistant", description="An AI assistant that helps with Bigpicture io 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 Bigpicture io 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 Bigpicture io 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 Bigpicture io session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["bigpicture_io"] ) 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 Bigpicture io assistant agent with MCP tools agent = AssistantAgent( name="bigpicture_io_assistant", description="An AI assistant that helps with Bigpicture io 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 Bigpicture io 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 Bigpicture io 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 Bigpicture io, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build Bigpicture io MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/bigpicture_io/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/bigpicture_io/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/bigpicture_io/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/bigpicture_io/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/bigpicture_io/framework/codex) - [OpenClaw](https://composio.dev/toolkits/bigpicture_io/framework/openclaw) - [Hermes](https://composio.dev/toolkits/bigpicture_io/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/bigpicture_io/framework/cli) - [Google ADK](https://composio.dev/toolkits/bigpicture_io/framework/google-adk) - [LangChain](https://composio.dev/toolkits/bigpicture_io/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/bigpicture_io/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/bigpicture_io/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/bigpicture_io/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/bigpicture_io/framework/crew-ai) ## Related Toolkits - [Excel](https://composio.dev/toolkits/excel) - Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. 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It helps streamline how you gather, organize, and analyze responses. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Bigpicture io MCP? With a standalone Bigpicture io MCP server, the agents and LLMs can only access a fixed set of Bigpicture io tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Bigpicture io 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 Bigpicture io tools. ### Can I manage the permissions and scopes for Bigpicture io while using Tool Router? Yes, absolutely. You can configure which Bigpicture io 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 Bigpicture io data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)