# How to integrate Cloudlayer MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Cloudlayer MCP with Vercel AI SDK v6", "toolkit": "Cloudlayer", "toolkit_slug": "cloudlayer", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/cloudlayer/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/cloudlayer/framework/ai-sdk.md", "updated_at": "2026-05-12T10:06:50.160Z" } ``` ## Introduction This guide walks you through connecting Cloudlayer to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Cloudlayer agent that can generate pdf from a contract html template, convert a marketing webpage to a png image, list your most recent generated assets through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Cloudlayer account through Composio's Cloudlayer MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Cloudlayer with - [OpenAI Agents SDK](https://composio.dev/toolkits/cloudlayer/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/cloudlayer/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/cloudlayer/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/cloudlayer/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/cloudlayer/framework/codex) - [OpenClaw](https://composio.dev/toolkits/cloudlayer/framework/openclaw) - [Hermes](https://composio.dev/toolkits/cloudlayer/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/cloudlayer/framework/cli) - [Google ADK](https://composio.dev/toolkits/cloudlayer/framework/google-adk) - [LangChain](https://composio.dev/toolkits/cloudlayer/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/cloudlayer/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/cloudlayer/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/cloudlayer/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Cloudlayer integration - Using Composio's Tool Router to dynamically load and access Cloudlayer 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 Cloudlayer MCP server, and what's possible with it? The Cloudlayer MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Cloudlayer account. It provides structured and secure access to dynamic document and asset generation, so your agent can perform actions like converting HTML or URLs to PDFs or images, managing assets, and configuring storage on your behalf. - Automated PDF and image generation: Instantly convert HTML content or public URLs into professional PDFs and images for reporting, documentation, or sharing. - Asset management and retrieval: Let your agent fetch metadata or download links for generated assets, or list your most recent document and image creations. - Dynamic storage configuration: Seamlessly add and manage external storage buckets or containers for organizing generated files and assets. - Real-time API health monitoring: Enable your agent to check Cloudlayer API status, ensuring your integrations are always up and running. - Flexible screenshot and rendering tasks: Capture dynamic webpage screenshots as images or PDFs, with full control over conversion parameters, for advanced automation workflows. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `CLOUDLAYER_ADD_STORAGE` | Add Storage | Add a user-owned S3-compatible storage configuration for storing generated assets. This action allows Enterprise plan users to configure their own S3-compatible storage (AWS S3, DigitalOcean Spaces, Wasabi, MinIO, etc.) instead of using the built-in cloud storage included with Cloudlayer accounts. Note: User storage is only available on Enterprise plans. Standard plans will receive an 'allowed: false' response indicating the feature requires a plan upgrade. | | `CLOUDLAYER_CONVERT_HTML_TO_IMAGE` | Convert HTML to Image (V2) | Convert HTML content to an image (PNG, JPG, or WebP) using the v2 API endpoint. Renders the provided HTML string using a headless browser and returns job details with the generated image asset. Supports various rendering options including viewport configuration, transparency, auto-scroll, and custom wait conditions. | | `CLOUDLAYER_CONVERT_HTML_TO_PDF_V2` | Convert HTML to PDF (v2) | Tool to convert HTML content to PDF using CloudLayer v2 API. Use when you need to generate a PDF from raw HTML with advanced options like custom paper size, margins, headers/footers, and viewport settings. The HTML is automatically Base64 encoded before sending to the API. | | `CLOUDLAYER_CONVERT_URL_TO_PDF_GET` | Convert URL to PDF (Simple) | Tool to convert a URL to PDF using GET request. Use when you need quick PDF conversion with minimal parameters and immediate result. | | `CLOUDLAYER_DELETE_STORAGE` | Delete Storage Configuration | Tool to delete a specific user storage configuration. Use when you need to remove an external bucket configuration by its ID after confirming the ID is correct. | | `CLOUDLAYER_GET_ACCOUNT_INFO` | Get Account Info | Tool to retrieve Cloudlayer account usage, credits, and document counts. Use when monitoring account limits and subscription status. | | `CLOUDLAYER_GET_ASSET` | Get Asset | Tool to retrieve a specific asset by its ID. Use when you need to fetch metadata or download URL of an existing asset after its generation. | | `CLOUDLAYER_GET_JOB_BY_ID` | Get Job By ID | Retrieve details of a specific Cloudlayer job by its ID. Use this to check the status of an async job, get the asset download URL after completion, or view job parameters. Returns 401 if the job ID doesn't exist or doesn't belong to your account. | | `CLOUDLAYER_GET_STATUS` | Get API Status | Tool to test API reachability. Use when checking if the Cloudlayer API is available. | | `CLOUDLAYER_GET_STORAGE_BY_ID` | Get Storage Configuration by ID | Tool to retrieve a specific storage configuration by its ID. Use when you need to inspect or validate details of a user storage configuration. | | `CLOUDLAYER_LIST_ASSETS` | List Assets | List assets in your CloudLayer account with cursor-based pagination. Returns PDFs and images generated via HTML/URL conversion jobs. Use this to find asset IDs for further operations like downloading or deleting assets. | | `CLOUDLAYER_LIST_JOBS` | List Jobs | List jobs in your CloudLayer account with cursor-based pagination. Use when you need to view your recent jobs and their statuses. | | `CLOUDLAYER_LIST_STORAGE` | List Storage Configurations | Retrieves all user storage configurations (S3-compatible buckets) for the authenticated Cloudlayer account. Use this to view configured external storage destinations where generated documents can be saved. Note: User Storage is an Enterprise plan feature. Non-Enterprise accounts will receive an empty list. | | `CLOUDLAYER_TEMPLATE_TO_PDF` | Template to PDF | Generate a PDF document from an HTML/Nunjucks template with dynamic data. Provide either: - A `templateId` for predefined templates from CloudLayer's template library, OR - A base64-encoded `template` string containing custom HTML/Nunjucks markup. The `data` parameter populates template variables (e.g., {{name}}, {{items}}) with your JSON data. By default, jobs run asynchronously and return a job ID to poll for completion via get_job_by_id. | | `CLOUDLAYER_URL_TO_IMAGE_POST` | Convert URL to Image | Converts a webpage URL to an image (PNG, JPG, or WebP). Supports custom viewport settings, wait conditions, transparency, auto-scroll, and thumbnail preview generation. The API is asynchronous - use the returned job ID to poll for results. | | `CLOUDLAYER_URL_TO_PDF_POST` | Convert URL to PDF | Tool to convert a URL to PDF with full parameter support. Use when you need advanced control over paper size, margins, headers/footers, or webhook callbacks. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Cloudlayer MCP server is an implementation of the Model Context Protocol that connects your AI agent to Cloudlayer. It provides structured and secure access so your agent can perform Cloudlayer 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 Cloudlayer 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 Cloudlayer-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: ["cloudlayer"], }); 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 Cloudlayer 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 cloudlayer, 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 Cloudlayer 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("\n๐Ÿ‘‹ 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: ["cloudlayer"], }); 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 cloudlayer, 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("\n๐Ÿ‘‹ Session ended."); process.exit(0); }); } main().catch((err) => { console.error("Fatal error:", err); process.exit(1); }); ``` ## Conclusion You've successfully built a Cloudlayer 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 Cloudlayer MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/cloudlayer/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/cloudlayer/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/cloudlayer/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/cloudlayer/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/cloudlayer/framework/codex) - [OpenClaw](https://composio.dev/toolkits/cloudlayer/framework/openclaw) - [Hermes](https://composio.dev/toolkits/cloudlayer/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/cloudlayer/framework/cli) - [Google ADK](https://composio.dev/toolkits/cloudlayer/framework/google-adk) - [LangChain](https://composio.dev/toolkits/cloudlayer/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/cloudlayer/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/cloudlayer/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/cloudlayer/framework/crew-ai) ## Related Toolkits - [Google Drive](https://composio.dev/toolkits/googledrive) - Google Drive is a cloud storage platform for uploading, sharing, and collaborating on files. It's perfect for keeping your documents accessible and organized across devices. - [Google Docs](https://composio.dev/toolkits/googledocs) - Google Docs is a cloud-based word processor that enables document creation and real-time collaboration. Its seamless sharing and version history make team editing and content management a breeze. - [Google Super](https://composio.dev/toolkits/googlesuper) - Google Super is an all-in-one suite combining Gmail, Drive, Calendar, Sheets, Analytics, and more. It gives you a unified platform to manage your digital life, boosting productivity and organization. - [Affinda](https://composio.dev/toolkits/affinda) - Affinda is an AI-powered document processing platform that automates data extraction from resumes, invoices, and more. It streamlines document-heavy workflows by turning files into structured, actionable data. - [Agility cms](https://composio.dev/toolkits/agility_cms) - Agility CMS is a headless content management system for building and managing digital experiences across platforms. It lets teams update content quickly and deliver omnichannel experiences with ease. - [Algodocs](https://composio.dev/toolkits/algodocs) - Algodocs is an AI-powered platform that automates data extraction from business documents. It delivers fast, secure, and accurate processing without templates or manual training. - [Api2pdf](https://composio.dev/toolkits/api2pdf) - Api2Pdf is a REST API for generating PDFs from HTML, URLs, and documents using powerful engines like wkhtmltopdf and Headless Chrome. It streamlines document conversion and automation for developers and businesses. - [Aryn](https://composio.dev/toolkits/aryn) - Aryn is an AI-powered platform for parsing, extracting, and analyzing data from unstructured documents. Use it to automate document processing and unlock actionable insights from your files. - [Boldsign](https://composio.dev/toolkits/boldsign) - Boldsign is a digital eSignature platform for sending, signing, and tracking documents online. Organizations use it to automate agreements and manage legally binding workflows efficiently. - [Boloforms](https://composio.dev/toolkits/boloforms) - BoloForms is an eSignature platform built for small businesses, offering unlimited signatures, templates, and forms. It simplifies digital document signing and team collaboration at a predictable, fixed price. - [Box](https://composio.dev/toolkits/box) - Box is a cloud content management and file sharing platform for businesses. It helps teams securely store, organize, and collaborate on files from anywhere. - [Carbone](https://composio.dev/toolkits/carbone) - Carbone is a blazing-fast report generator that turns JSON data into PDFs, Word docs, spreadsheets, and more using flexible templates. It lets you automate document creation at scale with minimal code. - [Castingwords](https://composio.dev/toolkits/castingwords) - CastingWords is a transcription service specializing in human-powered, accurate transcripts via a simple API. Get seamless audio-to-text conversion for interviews, meetings, podcasts, and more. - [Cloudconvert](https://composio.dev/toolkits/cloudconvert) - CloudConvert is a powerful file conversion service supporting over 200 file formats. It streamlines converting, compressing, and managing documents, media, and more, all in one place. - [Cloudpress](https://composio.dev/toolkits/cloudpress) - Cloudpress is a content export tool for Google Docs and Notion. It automates publishing to your favorite Content Management Systems. - [Contentful graphql](https://composio.dev/toolkits/contentful_graphql) - Contentful graphql is a content delivery API that lets you access Contentful data using GraphQL queries. It gives you efficient, flexible ways to fetch and manage structured content for any digital project. - [Conversion tools](https://composio.dev/toolkits/conversion_tools) - Conversion Tools is an online service for converting documents between formats such as PDF, Word, Excel, XML, and CSV. It lets you automate complex document workflows with just a few clicks. - [Convertapi](https://composio.dev/toolkits/convertapi) - ConvertAPI is a robust file conversion service for documents, images, and spreadsheets. It streamlines programmatic format changes and lets developers automate complex workflows with a single API. - [Craftmypdf](https://composio.dev/toolkits/craftmypdf) - CraftMyPDF is a web-based service for designing and generating PDFs with templates and live data. It streamlines document creation by automating personalized PDFs at scale. - [Docmosis](https://composio.dev/toolkits/docmosis) - Docmosis generates PDF and Word documents from user-defined templates. It's perfect for merging data fields to quickly produce reports, invoices, and business letters. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Cloudlayer MCP? With a standalone Cloudlayer MCP server, the agents and LLMs can only access a fixed set of Cloudlayer tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Cloudlayer 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 Cloudlayer tools. ### Can I manage the permissions and scopes for Cloudlayer while using Tool Router? Yes, absolutely. You can configure which Cloudlayer 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 Cloudlayer 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)