# How to integrate RudderStack Transformation MCP with Vercel AI SDK v6

```json
{
  "title": "How to integrate RudderStack Transformation MCP with Vercel AI SDK v6",
  "toolkit": "RudderStack Transformation",
  "toolkit_slug": "rudderstack_transformation",
  "framework": "Vercel AI SDK",
  "framework_slug": "ai-sdk",
  "url": "https://composio.dev/toolkits/rudderstack_transformation/framework/ai-sdk",
  "markdown_url": "https://composio.dev/toolkits/rudderstack_transformation/framework/ai-sdk.md",
  "updated_at": "2026-03-29T06:48:30.658Z"
}
```

## Introduction

This guide walks you through connecting RudderStack Transformation to Vercel AI SDK v6 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 Vercel AI SDK 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)
- [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 and configure a Vercel AI SDK agent with RudderStack Transformation integration
- Using Composio's Tool Router to dynamically load and access RudderStack Transformation tools
- Creating an MCP client connection using HTTP transport
- Building an interactive CLI chat interface with conversation history management
- Handling tool calls and results within the Vercel AI SDK framework

## What is Vercel AI SDK?

The Vercel AI SDK is a TypeScript library for building AI-powered applications. It provides tools for creating agents that can use external services and maintain conversation state.
Key features include:
- streamText: Core function for streaming responses with real-time tool support
- MCP Client: Built-in support for Model Context Protocol via @ai-sdk/mcp
- Step Counting: Control multi-step tool execution with stopWhen: stepCountIs()
- OpenAI Provider: Native integration with OpenAI models

## 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 you begin, make sure you have:
- Node.js and npm installed
- A Composio account with API key
- An OpenAI API key

### 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 required dependencies

First, install the necessary packages for your project.
What you're installing:
- @ai-sdk/openai: Vercel AI SDK's OpenAI provider
- @ai-sdk/mcp: MCP client for Vercel AI SDK
- @composio/core: Composio SDK for tool integration
- ai: Core Vercel AI SDK
- dotenv: Environment variable management
```bash
npm install @ai-sdk/openai @ai-sdk/mcp @composio/core ai dotenv
```

### 3. Set up environment variables

Create a .env file in your project root.
What's needed:
- OPENAI_API_KEY: Your OpenAI API key for GPT model access
- COMPOSIO_API_KEY: Your Composio API key for tool access
- COMPOSIO_USER_ID: A unique identifier for the user session
```bash
OPENAI_API_KEY=your_openai_api_key_here
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here
```

### 4. Import required modules and validate environment

What's happening:
- We're importing all necessary libraries including Vercel AI SDK's OpenAI provider and Composio
- The dotenv/config import automatically loads environment variables
- The MCP client import enables connection to Composio's tool server
```typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Composio } from "@composio/core";
import * as readline from "readline";
import { streamText, type ModelMessage, stepCountIs } from "ai";
import { createMCPClient } from "@ai-sdk/mcp";

const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey,
});
```

### 5. Create Tool Router session and initialize MCP client

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 mcp object contains the URL and authentication headers needed to connect to the MCP server
- This session provides access to all RudderStack Transformation-related tools through the MCP protocol
```typescript
async function main() {
  // Create a tool router session for the user
  const session = await composio.create(composioUserID!, {
    toolkits: ["rudderstack_transformation"],
  });

  const mcpUrl = session.mcp.url;
```

### 6. Connect to MCP server and retrieve tools

What's happening:
- We're creating an MCP client that connects to our Composio Tool Router session via HTTP
- The mcp.url provides the endpoint, and mcp.headers contains authentication credentials
- The type: "http" is important - Composio requires HTTP transport
- tools() retrieves all available RudderStack Transformation tools that the agent can use
```typescript
const mcpClient = await createMCPClient({
  transport: {
    type: "http",
    url: mcpUrl,
    headers: session.mcp.headers, // Authentication headers for the Composio MCP server
  },
});

const tools = await mcpClient.tools();
```

### 7. Initialize conversation and CLI interface

What's happening:
- We initialize an empty messages array to maintain conversation history
- A readline interface is created to accept user input from the command line
- Instructions are displayed to guide the user on how to interact with the agent
```typescript
let messages: ModelMessage[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log(
  "Ask any questions related to rudderstack_transformation, like summarize my last 5 emails, send an email, etc... :)))\n",
);

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: "> ",
});

rl.prompt();
```

### 8. Handle user input and stream responses with real-time tool feedback

What's happening:
- We use streamText instead of generateText to stream responses in real-time
- toolChoice: "auto" allows the model to decide when to use RudderStack Transformation tools
- stopWhen: stepCountIs(10) allows up to 10 steps for complex multi-tool operations
- onStepFinish callback displays which tools are being used in real-time
- We iterate through the text stream to create a typewriter effect as the agent responds
- The complete response is added to conversation history to maintain context
- Errors are caught and displayed with helpful retry suggestions
```typescript
rl.on("line", async (userInput: string) => {
  const trimmedInput = userInput.trim();

  if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
    console.log("\nGoodbye!");
    rl.close();
    process.exit(0);
  }

  if (!trimmedInput) {
    rl.prompt();
    return;
  }

  messages.push({ role: "user", content: trimmedInput });
  console.log("\nAgent is thinking...\n");

  try {
    const stream = streamText({
      model: openai("gpt-5"),
      messages,
      tools,
      toolChoice: "auto",
      stopWhen: stepCountIs(10),
      onStepFinish: (step) => {
        for (const toolCall of step.toolCalls) {
          console.log(`[Using tool: ${toolCall.toolName}]`);
          }
          if (step.toolCalls.length > 0) {
            console.log(""); // Add space after tool calls
          }
        },
      });

      for await (const chunk of stream.textStream) {
        process.stdout.write(chunk);
      }

      console.log("\n\n---\n");

      // Get final result for message history
      const response = await stream.response;
      if (response?.messages?.length) {
        messages.push(...response.messages);
      }
    } catch (error) {
      console.error("\nAn error occurred while talking to the agent:");
      console.error(error);
      console.log(
        "\nYou can try again or restart the app if it keeps happening.\n",
      );
    } finally {
      rl.prompt();
    }
  });

  rl.on("close", async () => {
    await mcpClient.close();
    console.log("\n👋 Session ended.");
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
```

## Complete Code

```typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Composio } from "@composio/core";
import * as readline from "readline";
import { streamText, type ModelMessage, stepCountIs } from "ai";
import { createMCPClient } from "@ai-sdk/mcp";

const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey,
});

async function main() {
  // Create a tool router session for the user
  const session = await composio.create(composioUserID!, {
    toolkits: ["rudderstack_transformation"],
  });

  const mcpUrl = session.mcp.url;

  const mcpClient = await createMCPClient({
    transport: {
      type: "http",
      url: mcpUrl,
      headers: session.mcp.headers, // Authentication headers for the Composio MCP server
    },
  });

  const tools = await mcpClient.tools();

  let messages: ModelMessage[] = [];

  console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
  console.log(
    "Ask any questions related to rudderstack_transformation, like summarize my last 5 emails, send an email, etc... :)))\n",
  );

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: "> ",
  });

  rl.prompt();

  rl.on("line", async (userInput: string) => {
    const trimmedInput = userInput.trim();

    if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
      console.log("\nGoodbye!");
      rl.close();
      process.exit(0);
    }

    if (!trimmedInput) {
      rl.prompt();
      return;
    }

    messages.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    try {
      const stream = streamText({
        model: openai("gpt-5"),
        messages,
        tools,
        toolChoice: "auto",
        stopWhen: stepCountIs(10),
        onStepFinish: (step) => {
          for (const toolCall of step.toolCalls) {
            console.log(`[Using tool: ${toolCall.toolName}]`);
          }
          if (step.toolCalls.length > 0) {
            console.log(""); // Add space after tool calls
          }
        },
      });

      for await (const chunk of stream.textStream) {
        process.stdout.write(chunk);
      }

      console.log("\n\n---\n");

      // Get final result for message history
      const response = await stream.response;
      if (response?.messages?.length) {
        messages.push(...response.messages);
      }
    } catch (error) {
      console.error("\nAn error occurred while talking to the agent:");
      console.error(error);
      console.log(
        "\nYou can try again or restart the app if it keeps happening.\n",
      );
    } finally {
      rl.prompt();
    }
  });

  rl.on("close", async () => {
    await mcpClient.close();
    console.log("\n👋 Session ended.");
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
```

## Conclusion

You've successfully built a RudderStack Transformation agent using the Vercel AI SDK with streaming capabilities! This implementation provides a powerful foundation for building AI applications with natural language interfaces and real-time feedback.
Key features of this implementation:
- Real-time streaming responses for a better user experience with typewriter effect
- Live tool execution feedback showing which tools are being used as the agent works
- Dynamic tool loading through Composio's Tool Router with secure authentication
- Multi-step tool execution with configurable step limits (up to 10 steps)
- Comprehensive error handling for robust agent execution
- Conversation history maintenance for context-aware responses
You can extend this further by adding custom error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

## 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)
- [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. It helps teams locate and filter information instantly, saving hours on research.
- [Exa](https://composio.dev/toolkits/exa) - Exa is a data extraction and search platform for gathering and analyzing information from websites, APIs, or databases. It helps teams quickly surface insights and automate data-driven workflows.
- [Serpapi](https://composio.dev/toolkits/serpapi) - SerpApi is a real-time API for structured search engine results. It lets you automate SERP data collection, parsing, and analysis for SEO and research.
- [Peopledatalabs](https://composio.dev/toolkits/peopledatalabs) - Peopledatalabs delivers B2B data enrichment and identity resolution APIs. Supercharge your apps with accurate, up-to-date business and contact data.
- [Snowflake](https://composio.dev/toolkits/snowflake) - Snowflake is a cloud data warehouse built for elastic scaling, secure data sharing, and fast SQL analytics across major clouds.
- [Posthog](https://composio.dev/toolkits/posthog) - PostHog is an open-source analytics platform for tracking user interactions and product metrics. It helps teams refine features, analyze funnels, and reduce churn with actionable insights.
- [Ably](https://composio.dev/toolkits/ably) - Ably is a real-time messaging platform for live chat and data sync in modern apps. It offers global scale and rock-solid reliability for seamless, instant experiences.
- [Abuselpdb](https://composio.dev/toolkits/abuselpdb) - Abuselpdb is a central database for reporting and checking IPs linked to malicious online activity. Use it to quickly identify and report suspicious or abusive IP addresses.
- [Alchemy](https://composio.dev/toolkits/alchemy) - Alchemy is a blockchain development platform offering APIs and tools for Ethereum apps. It simplifies building and scaling Web3 projects with robust infrastructure.
- [Algolia](https://composio.dev/toolkits/algolia) - Algolia is a hosted search API that powers lightning-fast, relevant search experiences for web and mobile apps. It helps developers deliver instant, typo-tolerant, and scalable search without complex infrastructure.
- [Amplitude](https://composio.dev/toolkits/amplitude) - Amplitude is a digital analytics platform for product and behavioral data insights. It helps teams analyze user journeys and make data-driven decisions quickly.
- [Anchor browser](https://composio.dev/toolkits/anchor_browser) - Anchor browser is a developer platform for AI-powered web automation. 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 Vercel AI SDK v6?

Yes, you can. Vercel AI SDK v6 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) · [Composio docs](https://docs.composio.dev/llms.txt)