# How to integrate RudderStack Transformation MCP with Pydantic AI ```json { "title": "How to integrate RudderStack Transformation MCP with Pydantic AI", "toolkit": "RudderStack Transformation", "toolkit_slug": "rudderstack_transformation", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/rudderstack_transformation/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/rudderstack_transformation/framework/pydantic-ai.md", "updated_at": "2026-03-29T06:48:30.658Z" } ``` ## Introduction This guide walks you through connecting RudderStack Transformation to Pydantic AI 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 Pydantic AI 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: - How to set up your Composio API key and User ID - How to create a Composio Tool Router session for RudderStack Transformation - How to attach an MCP Server to a Pydantic AI agent - How to stream responses and maintain chat history - How to build a simple REPL-style chat interface to test your RudderStack Transformation workflows ## What is Pydantic AI? Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications. Key features include: - Type Safety: Built on Pydantic for automatic data validation - MCP Support: Native support for Model Context Protocol servers - Streaming: Built-in support for streaming responses - Async First: Designed for async/await patterns ## 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 agent to RudderStack Transformation. It provides structured and secure access so your agent can perform RudderStack Transformation operations on your behalf through a secure, permission-based interface. 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 Before starting, make sure you have: - Python 3.9 or higher - A Composio account with an active API key - Basic familiarity with Python and async programming ### 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 the required libraries. What's happening: - composio connects your agent to external SaaS tools like RudderStack Transformation - pydantic-ai lets you create structured AI agents with tool support - python-dotenv loads your environment variables securely from a .env file ```bash pip install composio pydantic-ai python-dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's happening: - COMPOSIO_API_KEY authenticates your agent to Composio's API - USER_ID associates your session with your account for secure tool access - OPENAI_API_KEY to access OpenAI LLMs ```bash COMPOSIO_API_KEY=your_composio_api_key_here USER_ID=your_user_id_here OPENAI_API_KEY=your_openai_api_key ``` ### 4. Import dependencies What's happening: - We load environment variables and import required modules - Composio manages connections to RudderStack Transformation - MCPServerStreamableHTTP connects to the RudderStack Transformation MCP server endpoint - Agent from Pydantic AI lets you define and run the AI assistant ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from pydantic_ai import Agent from pydantic_ai.mcp import MCPServerStreamableHTTP load_dotenv() ``` ### 5. Create a Tool Router Session What's happening: - We're creating a Tool Router session that gives your agent access to RudderStack Transformation tools - The create method takes the user ID and specifies which toolkits should be available - The returned session.mcp.url is the MCP server URL that your agent will use ```python async def main(): api_key = os.getenv("COMPOSIO_API_KEY") user_id = os.getenv("USER_ID") if not api_key or not user_id: raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment") # Create a Composio Tool Router session for RudderStack Transformation composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["rudderstack_transformation"], ) url = session.mcp.url if not url: raise ValueError("Composio session did not return an MCP URL") ``` ### 6. Initialize the Pydantic AI Agent What's happening: - The MCP client connects to the RudderStack Transformation endpoint - The agent uses GPT-5 to interpret user commands and perform RudderStack Transformation operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent rudderstack_transformation_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[rudderstack_transformation_mcp], instructions=( "You are a RudderStack Transformation assistant. Use RudderStack Transformation tools to help users " "with their requests. Ask clarifying questions when needed." ), ) ``` ### 7. Build the chat interface What's happening: - The agent reads input from the terminal and streams its response - RudderStack Transformation API calls happen automatically under the hood - The model keeps conversation history to maintain context across turns ```python # Simple REPL with message history history = [] print("Chat started! Type 'exit' or 'quit' to end.\n") print("Try asking the agent to help you with RudderStack Transformation.\n") 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", flush=True) async with agent.run_stream(user_input, message_history=history) as stream_result: collected_text = "" async for chunk in stream_result.stream_output(): text_piece = None if isinstance(chunk, str): text_piece = chunk elif hasattr(chunk, "delta") and isinstance(chunk.delta, str): text_piece = chunk.delta elif hasattr(chunk, "text"): text_piece = chunk.text if text_piece: collected_text += text_piece result = stream_result print(f"Agent: {collected_text}\n") history = result.all_messages() ``` ### 8. Run the application What's happening: - The asyncio loop launches the agent and keeps it running until you exit ```python if __name__ == "__main__": asyncio.run(main()) ``` ## Complete Code ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from pydantic_ai import Agent from pydantic_ai.mcp import MCPServerStreamableHTTP load_dotenv() async def main(): api_key = os.getenv("COMPOSIO_API_KEY") user_id = os.getenv("USER_ID") if not api_key or not user_id: raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment") # Create a Composio Tool Router session for RudderStack Transformation composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["rudderstack_transformation"], ) url = session.mcp.url if not url: raise ValueError("Composio session did not return an MCP URL") # Attach the MCP server to a Pydantic AI Agent rudderstack_transformation_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[rudderstack_transformation_mcp], instructions=( "You are a RudderStack Transformation assistant. Use RudderStack Transformation tools to help users " "with their requests. Ask clarifying questions when needed." ), ) # Simple REPL with message history history = [] print("Chat started! Type 'exit' or 'quit' to end.\n") print("Try asking the agent to help you with RudderStack Transformation.\n") 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", flush=True) async with agent.run_stream(user_input, message_history=history) as stream_result: collected_text = "" async for chunk in stream_result.stream_output(): text_piece = None if isinstance(chunk, str): text_piece = chunk elif hasattr(chunk, "delta") and isinstance(chunk.delta, str): text_piece = chunk.delta elif hasattr(chunk, "text"): text_piece = chunk.text if text_piece: collected_text += text_piece result = stream_result print(f"Agent: {collected_text}\n") history = result.all_messages() if __name__ == "__main__": asyncio.run(main()) ``` ## Conclusion You've built a Pydantic AI agent that can interact with RudderStack Transformation through Composio's Tool Router. With this setup, your agent can perform real RudderStack Transformation actions through natural language. You can extend this further by: - Adding other toolkits like Gmail, HubSpot, or Salesforce - Building a web-based chat interface around this agent - Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + RudderStack Transformation for workflow automation) This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations. ## 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. It lets developers build modern apps without managing infrastructure. - [Codeinterpreter](https://composio.dev/toolkits/codeinterpreter) - Codeinterpreter is a Python-based coding environment with built-in data analysis and visualization. It lets you instantly run scripts, plot results, and prototype solutions inside supported platforms. - [GitHub](https://composio.dev/toolkits/github) - GitHub is a code hosting platform for version control and collaborative software development. It streamlines project management, code review, and team workflows in one place. - [Firecrawl](https://composio.dev/toolkits/firecrawl) - Firecrawl automates large-scale web crawling and data extraction. It helps organizations efficiently gather, index, and analyze content from online sources. - [Tavily](https://composio.dev/toolkits/tavily) - Tavily offers powerful search and data retrieval from documents, databases, and the web. 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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 Pydantic AI? Yes, you can. Pydantic AI 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)