# How to integrate Cats MCP with Autogen ```json { "title": "How to integrate Cats MCP with Autogen", "toolkit": "Cats", "toolkit_slug": "cats", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/cats/framework/autogen", "markdown_url": "https://composio.dev/toolkits/cats/framework/autogen.md", "updated_at": "2026-05-12T10:05:49.695Z" } ``` ## Introduction This guide walks you through connecting Cats to AutoGen using the Composio tool router. By the end, you'll have a working Cats agent that can show me five random cat images, list popular cat breeds with photos, find unique cat facts for trivia through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Cats account through Composio's Cats MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Cats with - [OpenAI Agents SDK](https://composio.dev/toolkits/cats/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/cats/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/cats/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/cats/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/cats/framework/codex) - [OpenClaw](https://composio.dev/toolkits/cats/framework/openclaw) - [Hermes](https://composio.dev/toolkits/cats/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/cats/framework/cli) - [Google ADK](https://composio.dev/toolkits/cats/framework/google-adk) - [LangChain](https://composio.dev/toolkits/cats/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/cats/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/cats/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/cats/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/cats/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 Cats - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Cats tools - Run a live chat loop where you ask the agent to perform Cats 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 Cats MCP server, and what's possible with it? The Cats MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Cats account. It provides structured and secure access to a wide collection of cat images, breed information, and fun feline facts, so your agent can fetch cat data, browse curated cat images, and pull breed details on your behalf. - Portals listing for cat resources: Instruct your agent to list and browse all available cat-related portals, making it easy to explore organized collections of cat images and data. - Metadata exploration with pagination: Have your agent efficiently page through vast cat collections, ensuring you can access just the right portal or dataset without missing a thing. - On-demand cat image discovery: Let your agent find and retrieve high-quality cat images from the API’s large, curated library—perfect for enrichment or just a dose of cuteness. - Access to detailed breed and fact data: Ask your agent to pull up detailed info on cat breeds and fun facts, making it a handy assistant for both research and entertainment. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `CATS_CREATE_FAVOURITE` | Create Favourite | Tool to save an image as a favourite to your account. Use when you want to mark a cat image as a favourite for later retrieval or filtering by user ID. | | `CATS_CREATE_VOTE` | Create Vote | Tool to vote on a cat image. Send image_id and value (1 for upvote, 0 for downvote) to register your vote. Optionally include sub_id for user tracking. | | `CATS_DELETE_FAVOURITE` | Delete Favourite | Tool to delete a favourite from your account by its ID. Use when you need to remove a previously saved favourite image from your Cat API account. | | `CATS_DELETE_IMAGE` | Delete Image | Delete an uploaded image from your account by its ID. Use this when you need to remove an image you previously uploaded to The Cat API. | | `CATS_DELETE_VOTE` | Delete Vote | Tool to delete a vote from your account by its ID. Use when you need to remove a previously submitted vote for a cat image. | | `CATS_GET_BREED` | Get Cat Breed by ID | Tool to get detailed information about a specific cat breed by its ID. Use when you need comprehensive details about a particular breed including temperament, origin, characteristics, and URLs. | | `CATS_GET_FAVOURITE` | Get Favourite by ID | Tool to retrieve a specific favourite by its unique ID. Returns full favourite details including user ID, image ID, creation timestamp, and associated image data. Use when you need to fetch a particular favourite's information or verify favourite existence. | | `CATS_GET_IMAGE` | Get Cat Image by ID | Tool to retrieve a specific cat image by its unique ID. Returns full image details including URL, dimensions, and breed information if available. Use when you need to fetch a particular image's data or verify image existence. | | `CATS_GET_IMAGE_ANALYSIS` | Get Image Analysis | Get machine learning analysis results for an uploaded image. Returns labels with confidence scores, bounding boxes for detected objects, and content moderation results from ML vendors. Note: GIF images are not supported for analysis. | | `CATS_GET_IMAGE_BREEDS` | Get Image Breeds | Tool to retrieve breed information associated with a specific cat image. Use when you need to identify which breed(s) are shown in a particular image from The Cat API. | | `CATS_GET_PORTALS` | Get Cat Breeds | Retrieves a paginated list of cat breeds from The Cat API. Returns comprehensive breed information including name, description, temperament, origin, life span, and weight. Use this to browse available cat breeds or search for specific breed information. | | `CATS_GET_VOTE` | Get Vote by ID | Retrieves a specific vote by its unique ID from The Cat API. Returns detailed vote information including the image ID, vote value, timestamp, and optional metadata like sub_id and country code. Use this when you need to fetch details about a specific vote. | | `CATS_LIST_CATEGORIES` | List Image Categories | Retrieves a list of all active image categories from The Cat API. Categories include hats, sunglasses, boxes, sinks, and more. Use category IDs when searching or filtering images by category. | | `CATS_LIST_FAVOURITES` | List Favourites | Tool to get all favourites belonging to your account. Use when you need to retrieve saved cat images, optionally filtered by sub_id. Supports pagination to browse through large collections of favourites. | | `CATS_LIST_UPLOADED_IMAGES` | List Uploaded Images | Tool to get all images uploaded to your account via /images/upload. Supports pagination and filtering by sub_id or original filename. Use this to retrieve your uploaded images, check if a file already exists, or filter by user identifiers. The API returns images in order of upload date. | | `CATS_LIST_VOTES` | List Votes | Tool to retrieve all votes you have created. Returns a paginated list of votes with image IDs, vote values, and metadata. Use this to view voting history, filter by user segment (sub_id), or analyze vote patterns. | | `CATS_SEARCH_BREEDS` | Search Cat Breeds | Search for cat breeds by name. Use the 'q' parameter with part or all of the breed name to find matching breeds. Returns breed details including temperament, origin, and characteristics. | | `CATS_SEARCH_IMAGES` | Search Cat Images | Search for random cat images with optional filters. Filter by breed availability, size, and file type. Returns an array of image objects with URLs and metadata. Use this to find cat images for display, testing, or content generation. The default behavior returns 1 random cat image. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Cats MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Cats. Instead of manually wiring Cats 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 Cats 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 Cats 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 Cats 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 Cats 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 Cats session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["cats"] ) 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 Cats 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 Cats assistant agent with MCP tools agent = AssistantAgent( name="cats_assistant", description="An AI assistant that helps with Cats 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 Cats 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 Cats 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 Cats session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["cats"] ) 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 Cats assistant agent with MCP tools agent = AssistantAgent( name="cats_assistant", description="An AI assistant that helps with Cats 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 Cats 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 Cats 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 Cats, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build Cats MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/cats/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/cats/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/cats/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/cats/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/cats/framework/codex) - [OpenClaw](https://composio.dev/toolkits/cats/framework/openclaw) - [Hermes](https://composio.dev/toolkits/cats/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/cats/framework/cli) - [Google ADK](https://composio.dev/toolkits/cats/framework/google-adk) - [LangChain](https://composio.dev/toolkits/cats/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/cats/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/cats/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/cats/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/cats/framework/crew-ai) ## Related Toolkits - [Youtube](https://composio.dev/toolkits/youtube) - YouTube is a leading video-sharing platform for uploading, streaming, and discovering content. It empowers creators and businesses to reach global audiences and monetize their work. - [Amara](https://composio.dev/toolkits/amara) - Amara is a collaborative platform for creating and managing subtitles and captions for videos. It helps make content accessible and multilingual for global audiences. - [Chatfai](https://composio.dev/toolkits/chatfai) - Chatfai is an AI platform that lets users talk to AI versions of fictional characters from books, movies, and games. It offers an engaging, interactive experience for fans to chat, roleplay, and explore creative dialogues. - [Cincopa](https://composio.dev/toolkits/cincopa) - Cincopa is a multimedia platform for uploading, managing, and customizing videos, images, and audio. It helps you deliver engaging media experiences with robust APIs and flexible integrations. - [Dungeon fighter online](https://composio.dev/toolkits/dungeon_fighter_online) - Dungeon Fighter Online (DFO) is an arcade-style, side-scrolling action RPG packed with dynamic combat and progression. Play solo or with friends to battle monsters, complete quests, and upgrade your characters. - [Elevenlabs](https://composio.dev/toolkits/elevenlabs) - Elevenlabs is an advanced AI voice generation platform for lifelike, multilingual speech synthesis. Perfect for creating natural voices for videos, apps, and business content in seconds. - [Elevenreader](https://composio.dev/toolkits/elevenreader) - Elevenreader is an AI-powered text-to-speech service by ElevenLabs that converts written content into lifelike audio. It enables fast, natural audio generation from any text. - [Epic games](https://composio.dev/toolkits/epic_games) - Epic Games is a leading video game publisher and digital storefront, known for Fortnite and Unreal Engine. It lets gamers access, manage, and purchase games all in one place. - [Fal.ai](https://composio.dev/toolkits/fal_ai) - Fal.ai is a generative media platform offering 600+ AI models for images, video, voice, and audio. Developers use Fal.ai for fast, scalable access to cutting-edge generative AI tools. - [Giphy](https://composio.dev/toolkits/giphy) - Giphy is the largest online library for searching and sharing GIFs and stickers. Instantly add vibrant animated content to your apps, chats, and workflows. - [Headout](https://composio.dev/toolkits/headout) - Headout is a global platform for booking travel experiences, tours, and entertainment. It helps users discover and secure activities at top destinations, all in one place. - [Imagekit io](https://composio.dev/toolkits/imagekit_io) - ImageKit.io is a cloud-based media management platform for image and video delivery. Instantly optimize, transform, and deliver visuals globally via a lightning-fast CDN. - [Listennotes](https://composio.dev/toolkits/listennotes) - Listennotes is a powerful podcast search engine with a massive global database. Discover, search, and curate podcasts from around the world in seconds. - [News api](https://composio.dev/toolkits/news_api) - News api is a REST API for searching and retrieving live news articles from across the web. Instantly access headlines, coverage, and breaking stories from thousands of sources. - [RAWG Video Games Database](https://composio.dev/toolkits/rawg_video_games_database) - RAWG Video Games Database is the largest video game discovery and info service. Instantly access comprehensive details, ratings, and release dates for thousands of games. - [Seat geek](https://composio.dev/toolkits/seat_geek) - SeatGeek is a live event platform offering APIs for concerts, sports, and theater data. Instantly access events, venues, and performers info for smarter ticketing and discovery. - [Shotstack](https://composio.dev/toolkits/shotstack) - Shotstack is a cloud platform for programmatically generating videos, images, and audio. Automate creative content production at scale with flexible RESTful APIs. - [Spotify](https://composio.dev/toolkits/spotify) - Spotify is a streaming service for music and podcasts with millions of tracks from artists worldwide. Enjoy personalized playlists, recommendations, and seamless listening across all your devices. - [Ticketmaster](https://composio.dev/toolkits/ticketmaster) - Ticketmaster is a global platform for event discovery, ticket sales, and live entertainment management. Get real-time access to events and streamline ticketing for fans and organizers. - [Gmail](https://composio.dev/toolkits/gmail) - Gmail is Google's email service with powerful spam protection, search, and G Suite integration. It keeps your inbox organized and makes communication fast and reliable. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Cats MCP? With a standalone Cats MCP server, the agents and LLMs can only access a fixed set of Cats tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Cats 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 Cats tools. ### Can I manage the permissions and scopes for Cats while using Tool Router? Yes, absolutely. You can configure which Cats 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 Cats data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)