# How to integrate Alttext ai MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Alttext ai MCP with Vercel AI SDK v6", "toolkit": "Alttext ai", "toolkit_slug": "alttext_ai", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/alttext_ai/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/alttext_ai/framework/ai-sdk.md", "updated_at": "2026-05-12T10:00:58.832Z" } ``` ## Introduction This guide walks you through connecting Alttext ai to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Alttext ai agent that can generate alt text for new uploaded image, list images missing alt descriptions, search images by keyword in alt text through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Alttext ai account through Composio's Alttext ai MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Alttext ai with - [OpenAI Agents SDK](https://composio.dev/toolkits/alttext_ai/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/alttext_ai/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/alttext_ai/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/alttext_ai/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/alttext_ai/framework/codex) - [OpenClaw](https://composio.dev/toolkits/alttext_ai/framework/openclaw) - [Hermes](https://composio.dev/toolkits/alttext_ai/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/alttext_ai/framework/cli) - [Google ADK](https://composio.dev/toolkits/alttext_ai/framework/google-adk) - [LangChain](https://composio.dev/toolkits/alttext_ai/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/alttext_ai/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/alttext_ai/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/alttext_ai/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Alttext ai integration - Using Composio's Tool Router to dynamically load and access Alttext ai 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 Alttext ai MCP server, and what's possible with it? The Alttext ai MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Alttext ai account. It provides structured and secure access to your image library and account, so your agent can retrieve images, generate and search alt text, update account settings, and manage your Alttext.ai workflow on your behalf. - Automated image library browsing: Instantly fetch and paginate through your stored images, complete with their alt text and metadata, to keep track of your visual assets. - Keyword-based image searches: Direct your agent to search your image collection and find specific images or alt text based on custom search terms or filters. - Account monitoring and insights: Check your Alttext.ai account configuration, review current usage limits, and monitor your plan details or webhook settings—no manual dashboard visits needed. - Account configuration management: Let your agent update your account details, such as webhook URLs or display names, to streamline your integration and notification setup. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `ALTTEXT_AI_CREATE_BULK_IMAGES` | Bulk Create Images | Tool to bulk upload and process a CSV file of image URLs for alt text generation. Use when you need to process multiple images at once (up to 100,000 URLs). Invalid rows are returned in row_errors for debugging. | | `ALTTEXT_AI_CREATE_IMAGE` | Create Image | Tool to add an image and generate alt text. Supports both URL and base64-encoded file upload. Use when you need to generate alt text for images, with options for custom prompts, keywords, multiple languages, and ecommerce data. Rate limited to 4 calls per second. | | `ALTTEXT_AI_DELETE_IMAGE_BY_ASSET_ID` | Delete Image by Asset ID | Tool to delete an image from your library by its asset ID. Use when you need to remove a specific image permanently from your AltText.ai account. | | `ALTTEXT_AI_GET_ACCOUNT` | Get Account | Tool to retrieve account settings and usage information. Use when you need to check your AltText.ai account configuration and usage limits before generating alt text. | | `ALTTEXT_AI_GET_IMAGE_BY_ASSET_ID` | Get Image by Asset ID | Tool to retrieve detailed information about a specific image using its asset ID. Use when you need to fetch alt text, metadata, or status of a previously processed image. | | `ALTTEXT_AI_GET_IMAGES` | Get Images | Tool to retrieve a paginated list of images in your library, including their alt text and metadata. Use when you need to browse or filter images programmatically after authentication. | | `ALTTEXT_AI_SCRAPE_PAGE` | Scrape Page for Images | Tool to scrape a web page or HTML document and queue all images for alt text generation. Images are processed asynchronously. Does not execute JavaScript. Use when you need to batch-process images from a website or HTML content. | | `ALTTEXT_AI_SEARCH_IMAGES` | Search Images | Search for images in your AltText.ai library by keywords. Searches through your previously processed images to find matches based on URLs, alt text content, and metadata. Useful for finding specific images in large libraries. Returns paginated results with alt text and metadata. Note: This searches your own image library, not a public image database. Images must be added via the Create Image endpoint before they can be searched. | | `ALTTEXT_AI_UPDATE_ACCOUNT` | Update Account | Tool to update account settings (e.g., webhook_url, name). Use after confirming current account details to modify settings. | | `ALTTEXT_AI_UPDATE_IMAGE_BY_ASSET_ID` | Update Image by Asset ID | Tool to update an image with new data including asset ID, alt text, and metadata. Use when you need to modify existing image information. Note: You cannot update the URL of an existing image. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Alttext ai MCP server is an implementation of the Model Context Protocol that connects your AI agent to Alttext ai. It provides structured and secure access so your agent can perform Alttext ai 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 Alttext ai 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 Alttext ai-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: ["alttext_ai"], }); 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 Alttext ai 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 alttext_ai, 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 Alttext ai 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: ["alttext_ai"], }); 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 alttext_ai, 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 Alttext ai 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 Alttext ai MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/alttext_ai/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/alttext_ai/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/alttext_ai/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/alttext_ai/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/alttext_ai/framework/codex) - [OpenClaw](https://composio.dev/toolkits/alttext_ai/framework/openclaw) - [Hermes](https://composio.dev/toolkits/alttext_ai/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/alttext_ai/framework/cli) - [Google ADK](https://composio.dev/toolkits/alttext_ai/framework/google-adk) - [LangChain](https://composio.dev/toolkits/alttext_ai/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/alttext_ai/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/alttext_ai/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/alttext_ai/framework/crew-ai) ## Related Toolkits - [Figma](https://composio.dev/toolkits/figma) - Figma is a collaborative interface design tool for teams and individuals. It streamlines design workflows with real-time collaboration and easy sharing. - [Abyssale](https://composio.dev/toolkits/abyssale) - Abyssale is a creative automation platform for generating images, videos, GIFs, PDFs, and HTML5 content programmatically. It streamlines and scales visual content production for marketing, design, and operations teams. - [Bannerbear](https://composio.dev/toolkits/bannerbear) - Bannerbear is an API-driven platform for generating images and videos automatically at scale. It helps businesses create custom graphics, social visuals, and marketing assets using powerful templates. - [Canva](https://composio.dev/toolkits/canva) - Canva is a drag-and-drop design suite for creating professional graphics, presentations, and marketing materials. It makes it easy for anyone to design with beautiful templates and a vast library of elements. - [Claid ai](https://composio.dev/toolkits/claid_ai) - Claid.ai delivers AI-driven image editing APIs for tasks like background removal, upscaling, and color correction. It helps automate and enhance image workflows with powerful, developer-friendly tools. - [Cloudinary](https://composio.dev/toolkits/cloudinary) - Cloudinary is a cloud-based platform for managing, uploading, and transforming images and videos. It streamlines media workflows and delivers optimized assets globally. - [Cults](https://composio.dev/toolkits/cults) - Cults is a digital marketplace for 3D printing models, connecting designers and makers. It lets creators share, sell, and discover a huge variety of printable designs easily. - [DeepImage](https://composio.dev/toolkits/deepimage) - DeepImage is an AI-powered image enhancer and upscaler. Get higher-quality images with just a few clicks. - [Dreamstudio](https://composio.dev/toolkits/dreamstudio) - DreamStudio is Stability AI’s platform for generating and editing images with AI. It lets you easily turn ideas into stunning visuals, fast. - [Dynapictures](https://composio.dev/toolkits/dynapictures) - Dynapictures is a cloud-based platform for generating personalized images at scale. Instantly create hundreds of custom visuals using your data sources, like Google Sheets. - [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. - [Gamma](https://composio.dev/toolkits/gamma) - Gamma is an AI-powered platform for making beautiful, interactive presentations and documents. It lets anyone create and share engaging decks with minimal effort. - [Html to image](https://composio.dev/toolkits/html_to_image) - Html to image converts HTML and CSS into images or captures web page screenshots. Instantly generate visuals from code or web content—no manual screenshots needed. - [Imagior](https://composio.dev/toolkits/imagior) - Imagior is an AI-powered image generation platform that lets you create and customize images using dynamic templates and APIs. Perfect for businesses and creators needing fast, scalable visuals without design hassle. - [Imejis io](https://composio.dev/toolkits/imejis_io) - Imejis io is an API-based image generation platform with powerful customization and template support. It lets you create and modify images in seconds, no manual design work required. - [Imgix](https://composio.dev/toolkits/imgix) - Imgix is a real-time image processing and delivery service for developers. It helps you optimize, transform, and deliver images efficiently at any scale. - [Kraken io](https://composio.dev/toolkits/kraken_io) - Kraken.io is an image optimization and compression platform. It helps you shrink image file sizes while keeping visual quality intact. - [Logo dev](https://composio.dev/toolkits/logo_dev) - Logo.dev is an API and database for high-resolution company logos and brand metadata. Instantly fetch official logos from any domain without scraping or manual searching. - [Miro](https://composio.dev/toolkits/miro) - Miro is a collaborative online whiteboard platform for teams to brainstorm, design, and manage projects visually. It streamlines teamwork by enabling real-time idea sharing, diagramming, and workflow planning in a single space. - [Mural](https://composio.dev/toolkits/mural) - Mural is a digital whiteboard platform for distributed visual collaboration. It helps teams brainstorm, map ideas, and diagram together in real time. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Alttext ai MCP? With a standalone Alttext ai MCP server, the agents and LLMs can only access a fixed set of Alttext ai tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Alttext ai 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 Alttext ai tools. ### Can I manage the permissions and scopes for Alttext ai while using Tool Router? Yes, absolutely. You can configure which Alttext ai 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 Alttext ai data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)