# How to integrate Uptimerobot MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Uptimerobot MCP with Vercel AI SDK v6", "toolkit": "Uptimerobot", "toolkit_slug": "uptimerobot", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/uptimerobot/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/uptimerobot/framework/ai-sdk.md", "updated_at": "2026-05-12T10:29:33.886Z" } ``` ## Introduction This guide walks you through connecting Uptimerobot to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Uptimerobot agent that can add a new monitor for your homepage, delete the monitor for staging site, edit the maintenance window for tonight through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Uptimerobot account through Composio's Uptimerobot MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Uptimerobot with - [OpenAI Agents SDK](https://composio.dev/toolkits/uptimerobot/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/uptimerobot/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/uptimerobot/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/uptimerobot/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/uptimerobot/framework/codex) - [OpenClaw](https://composio.dev/toolkits/uptimerobot/framework/openclaw) - [Hermes](https://composio.dev/toolkits/uptimerobot/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/uptimerobot/framework/cli) - [Google ADK](https://composio.dev/toolkits/uptimerobot/framework/google-adk) - [LangChain](https://composio.dev/toolkits/uptimerobot/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/uptimerobot/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/uptimerobot/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/uptimerobot/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Uptimerobot integration - Using Composio's Tool Router to dynamically load and access Uptimerobot 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 Uptimerobot MCP server, and what's possible with it? The Uptimerobot MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Uptimerobot account. It provides structured and secure access to your monitoring dashboard, so your agent can perform actions like creating monitors, managing maintenance windows, retrieving account details, and updating public status pages on your behalf. - Automated monitor management: Easily add, edit, or delete monitors for your websites, applications, or services without manual dashboard navigation. - Maintenance window control: Let your agent fetch, edit, or update maintenance windows to schedule downtime or maintenance periods programmatically. - Public status page updates: Directly modify the configuration and details of your public status pages to keep stakeholders informed in real time. - Account and performance insights: Retrieve comprehensive account metrics, including details about your monitors and overall uptime statistics, with a simple agent request. - Monitor authentication and headers management: Inspect or adjust authentication types, custom HTTP headers, and HTTP status codes for your monitors for advanced configuration and troubleshooting. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `UPTIMEROBOT_ADD_MONITOR` | Add Monitor | Tool to create a new monitor. Use when you need to start monitoring a URL or service; call after obtaining a valid API key. | | `UPTIMEROBOT_DELETE_MONITOR` | Delete Monitor | Tool to delete a monitor. Use when you need to remove an existing monitor by its ID; use after confirming the monitor ID. | | `UPTIMEROBOT_EDIT_MAINTENANCE_WINDOW` | Edit Maintenance Window | Tool to edit an existing maintenance window. Use when you need to update its name, timing, recurrence, or duration after confirming the window ID. | | `UPTIMEROBOT_EDIT_MONITOR` | Edit Monitor | Tool to edit an existing monitor. Use after confirming the monitor ID exists. | | `UPTIMEROBOT_EDIT_PUBLIC_STATUS_PAGE` | Edit Public Status Page | Tool to edit an existing public status page. Use after confirming the page ID. Updates friendly name, monitor set, domain, and status options in one call. | | `UPTIMEROBOT_GET_ACCOUNT_DETAILS` | Get Account Details | Tool to retrieve account details. Use after authenticating with a valid API key to fetch account metrics. | | `UPTIMEROBOT_GET_ALERT_CONTACTS` | Get Alert Contacts | Tool to retrieve all alert contacts configured for the account. Use when you need to list available notification channels. | | `UPTIMEROBOT_GET_MAINTENANCE_WINDOW` | Get Maintenance Window | Tool to retrieve a specific maintenance window by ID. Use when you need to get detailed information about a single maintenance window. | | `UPTIMEROBOT_GET_MAINTENANCE_WINDOWS` | Get Maintenance Windows | Tool to retrieve maintenance windows. Use after confirming a valid API key. | | `UPTIMEROBOT_GET_MONITORS` | Get Monitors | Tool to fetch monitor details and status. Use after confirming account connection. | | `UPTIMEROBOT_GET_PUBLIC_STATUS_PAGES` | Get Public Status Pages | Tool to retrieve public status pages. Use after confirming API credentials to list all public status pages for an account. Supports pagination. | | `UPTIMEROBOT_LIST_INTEGRATIONS` | List Integrations | Tool to list all integrations. Use to retrieve configured integrations for the account. | | `UPTIMEROBOT_LIST_PSPS` | List Public Status Pages (v3) | Tool to list public status pages using the v3 API. Use to retrieve all PSPs with cursor-based pagination. | | `UPTIMEROBOT_NEW_MAINTENANCE_WINDOW` | New Maintenance Window | Tool to create a new maintenance window. Use after confirming window parameters. | | `UPTIMEROBOT_NEW_PUBLIC_STATUS_PAGE` | New Public Status Page | Tool to create a new public status page. Use when you want to publish a public status page for selected monitors after specifying a friendly name. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Uptimerobot MCP server is an implementation of the Model Context Protocol that connects your AI agent to Uptimerobot. It provides structured and secure access so your agent can perform Uptimerobot 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 Uptimerobot 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 Uptimerobot-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: ["uptimerobot"], }); 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 Uptimerobot 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 uptimerobot, 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 Uptimerobot 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: ["uptimerobot"], }); 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 uptimerobot, 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 Uptimerobot 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 Uptimerobot MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/uptimerobot/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/uptimerobot/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/uptimerobot/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/uptimerobot/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/uptimerobot/framework/codex) - [OpenClaw](https://composio.dev/toolkits/uptimerobot/framework/openclaw) - [Hermes](https://composio.dev/toolkits/uptimerobot/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/uptimerobot/framework/cli) - [Google ADK](https://composio.dev/toolkits/uptimerobot/framework/google-adk) - [LangChain](https://composio.dev/toolkits/uptimerobot/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/uptimerobot/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/uptimerobot/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/uptimerobot/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. - [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. - [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. - [Appveyor](https://composio.dev/toolkits/appveyor) - AppVeyor is a cloud-based continuous integration service for building, testing, and deploying applications. It helps developers automate and streamline their software delivery pipelines. - [Backendless](https://composio.dev/toolkits/backendless) - Backendless is a backend-as-a-service platform for mobile and web apps, offering database, file storage, user authentication, and APIs. It helps developers ship scalable applications faster without managing server infrastructure. - [Baserow](https://composio.dev/toolkits/baserow) - Baserow is an open-source no-code database platform for building collaborative data apps. It makes it easy for teams to organize data and automate workflows without writing code. - [Bench](https://composio.dev/toolkits/bench) - Bench is a benchmarking tool for automated performance measurement and analysis. It helps you quickly evaluate, compare, and track your systems or workflows. - [Better stack](https://composio.dev/toolkits/better_stack) - Better Stack is a monitoring, logging, and incident management solution for apps and services. It helps teams ensure application reliability and performance with real-time insights. - [Bitbucket](https://composio.dev/toolkits/bitbucket) - Bitbucket is a Git-based code hosting and collaboration platform for teams. It enables secure repository management and streamlined code reviews. - [Blazemeter](https://composio.dev/toolkits/blazemeter) - Blazemeter is a continuous testing platform for web and mobile app performance. It empowers teams to automate and analyze large-scale tests with ease. - [Blocknative](https://composio.dev/toolkits/blocknative) - Blocknative delivers real-time mempool monitoring and transaction management for public blockchains. Instantly track pending transactions and optimize blockchain interactions with live data. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Uptimerobot MCP? With a standalone Uptimerobot MCP server, the agents and LLMs can only access a fixed set of Uptimerobot tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Uptimerobot 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 Uptimerobot tools. ### Can I manage the permissions and scopes for Uptimerobot while using Tool Router? Yes, absolutely. You can configure which Uptimerobot 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 Uptimerobot 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)