# How to integrate RudderStack Transformation MCP with Autogen ```json { "title": "How to integrate RudderStack Transformation MCP with Autogen", "toolkit": "RudderStack Transformation", "toolkit_slug": "rudderstack_transformation", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/rudderstack_transformation/framework/autogen", "markdown_url": "https://composio.dev/toolkits/rudderstack_transformation/framework/autogen.md", "updated_at": "2026-03-29T06:48:30.658Z" } ``` ## Introduction This guide walks you through connecting RudderStack Transformation to AutoGen using the Composio tool router. By the end, you'll have a working RudderStack Transformation agent that can list all transformations for workspace marketing-pipeline, update the transformation script for user-events, delete transformation named old-data-cleanup through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a RudderStack Transformation account through Composio's RudderStack Transformation MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate RudderStack Transformation with - [OpenAI Agents SDK](https://composio.dev/toolkits/rudderstack_transformation/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/rudderstack_transformation/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/rudderstack_transformation/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/rudderstack_transformation/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/rudderstack_transformation/framework/codex) - [OpenClaw](https://composio.dev/toolkits/rudderstack_transformation/framework/openclaw) - [Hermes](https://composio.dev/toolkits/rudderstack_transformation/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/rudderstack_transformation/framework/cli) - [Google ADK](https://composio.dev/toolkits/rudderstack_transformation/framework/google-adk) - [LangChain](https://composio.dev/toolkits/rudderstack_transformation/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/rudderstack_transformation/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/rudderstack_transformation/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/rudderstack_transformation/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/rudderstack_transformation/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 RudderStack Transformation - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call RudderStack Transformation tools - Run a live chat loop where you ask the agent to perform RudderStack Transformation 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 RudderStack Transformation MCP server, and what's possible with it? The RudderStack Transformation MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your RudderStack Transformation account. It provides structured and secure access so your agent can perform RudderStack Transformation operations on your behalf. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `RUDDERSTACK_TRANSFORMATION_CREATE_LIBRARY` | Create Library | Tool to create a library in RudderStack Transformation. Use when you need to create reusable JavaScript or Python code that can be imported in transformations. Libraries enable code reusability and version maintenance. | | `RUDDERSTACK_TRANSFORMATION_CREATE_TRANSFORMATION` | Create Transformation | Tool to create a RudderStack transformation. When publish=false (default), creates an unpublished transformation not available to event traffic. When publish=true, publishes the transformation making it live for incoming events and connectable to destinations. | | `RUDDERSTACK_TRANSFORMATION_DELETE_TRANSFORMATION` | Delete Transformation | Delete a published transformation by ID. Note that RudderStack never deletes a transformation revision. Use this when you need to remove a transformation from the system. | | `RUDDERSTACK_TRANSFORMATION_GET_LIBRARY` | Get library by ID | Retrieves a single published library by its unique identifier. Use when you need to fetch details of a specific library. | | `RUDDERSTACK_TRANSFORMATION_GET_LIBRARY_VERSION` | Get Library Version | Tool to retrieve a single library version by library ID and version ID. Use when you need to fetch details of a specific library revision in RudderStack transformations. | | `RUDDERSTACK_TRANSFORMATION_GET_TRANSFORMATION` | Get Transformation | Tool to retrieve a published transformation by its ID from RudderStack. Use when you need to fetch details about a specific transformation including its code, version, and associated destinations. | | `RUDDERSTACK_TRANSFORMATION_GET_TRANSFORMATION_VERSION` | Get Transformation Version | Retrieve a single transformation revision by transformation ID and version ID. Use when you need to get details about a specific version of a RudderStack transformation. | | `RUDDERSTACK_TRANSFORMATION_LIST_ALL_LIBRARIES` | List All Libraries | Tool to retrieve all published libraries for a workspace. Use when you need to list available libraries for transformations. | | `RUDDERSTACK_TRANSFORMATION_LIST_LIBRARY_VERSIONS` | List Library Versions | Tool to get all library revisions for a library ID. Use when you need to retrieve all versions of a specific library in RudderStack Transformation. | | `RUDDERSTACK_TRANSFORMATION_LIST_ALL_TRANSFORMATIONS` | List All Transformations | Tool to retrieve all published transformations for a workspace. Use when you need to list available transformations or find a specific transformation by name. | | `RUDDERSTACK_TRANSFORMATION_LIST_TRANSFORMATION_VERSIONS` | List Transformation Versions | Tool to list all transformation versions (revisions) for a given transformation ID. Use when you need to retrieve the version history of a specific transformation. | | `RUDDERSTACK_TRANSFORMATION_UPDATE_TRANSFORMATION` | Update Transformation | Tool to update and optionally publish a RudderStack transformation. Use when you need to modify a transformation's name, description, or code. Updating creates a new revision and sets it as published if the publish flag is true. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The RudderStack Transformation MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to RudderStack Transformation. Instead of manually wiring RudderStack Transformation 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 RudderStack Transformation 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 RudderStack Transformation 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 RudderStack Transformation 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 RudderStack Transformation 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 RudderStack Transformation session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["rudderstack_transformation"] ) 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 RudderStack Transformation 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 RudderStack Transformation assistant agent with MCP tools agent = AssistantAgent( name="rudderstack_transformation_assistant", description="An AI assistant that helps with RudderStack Transformation 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 RudderStack Transformation 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 RudderStack Transformation 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 RudderStack Transformation session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["rudderstack_transformation"] ) 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 RudderStack Transformation assistant agent with MCP tools agent = AssistantAgent( name="rudderstack_transformation_assistant", description="An AI assistant that helps with RudderStack Transformation 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 RudderStack Transformation 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 RudderStack Transformation 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 RudderStack Transformation, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build RudderStack Transformation MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/rudderstack_transformation/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/rudderstack_transformation/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/rudderstack_transformation/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/rudderstack_transformation/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/rudderstack_transformation/framework/codex) - [OpenClaw](https://composio.dev/toolkits/rudderstack_transformation/framework/openclaw) - [Hermes](https://composio.dev/toolkits/rudderstack_transformation/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/rudderstack_transformation/framework/cli) - [Google ADK](https://composio.dev/toolkits/rudderstack_transformation/framework/google-adk) - [LangChain](https://composio.dev/toolkits/rudderstack_transformation/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/rudderstack_transformation/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/rudderstack_transformation/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/rudderstack_transformation/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/rudderstack_transformation/framework/crew-ai) ## Related Toolkits - [Supabase](https://composio.dev/toolkits/supabase) - Supabase is an open-source backend platform offering scalable Postgres databases, authentication, storage, and real-time APIs. 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It transforms complex browser actions into easy API endpoints for streamlined web interaction. - [Apiflash](https://composio.dev/toolkits/apiflash) - Apiflash is a website screenshot API for programmatically capturing web pages. It delivers high-quality screenshots on demand for automation, monitoring, or reporting. - [Apiverve](https://composio.dev/toolkits/apiverve) - Apiverve delivers a suite of powerful APIs that simplify integration for developers. It's designed for reliability and scalability so you can build faster, smarter applications without the integration headache. - [Appcircle](https://composio.dev/toolkits/appcircle) - Appcircle is an enterprise-grade mobile CI/CD platform for building, testing, and publishing mobile apps. It streamlines mobile DevOps so teams ship faster and with more confidence. - [Appdrag](https://composio.dev/toolkits/appdrag) - Appdrag is a cloud platform for building websites, APIs, and databases with drag-and-drop tools and code editing. It accelerates development and iteration by combining hosting, database management, and low-code features in one place. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and RudderStack Transformation MCP? With a standalone RudderStack Transformation MCP server, the agents and LLMs can only access a fixed set of RudderStack Transformation tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from RudderStack Transformation 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 RudderStack Transformation tools. ### Can I manage the permissions and scopes for RudderStack Transformation while using Tool Router? Yes, absolutely. You can configure which RudderStack Transformation 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 RudderStack Transformation data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) ยท [Composio docs](https://docs.composio.dev/llms.txt)