# How to integrate Iqair airvisual MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Iqair airvisual MCP with Vercel AI SDK v6", "toolkit": "Iqair airvisual", "toolkit_slug": "iqair_airvisual", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/iqair_airvisual/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/iqair_airvisual/framework/ai-sdk.md", "updated_at": "2026-05-12T10:16:23.019Z" } ``` ## Introduction This guide walks you through connecting Iqair airvisual to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Iqair airvisual agent that can show today's air quality in los angeles, list cities in maharashtra, india with data, get historical aqi for paris last week through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Iqair airvisual account through Composio's Iqair airvisual MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Iqair airvisual with - [OpenAI Agents SDK](https://composio.dev/toolkits/iqair_airvisual/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/iqair_airvisual/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/iqair_airvisual/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/iqair_airvisual/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/iqair_airvisual/framework/codex) - [OpenClaw](https://composio.dev/toolkits/iqair_airvisual/framework/openclaw) - [Hermes](https://composio.dev/toolkits/iqair_airvisual/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/iqair_airvisual/framework/cli) - [Google ADK](https://composio.dev/toolkits/iqair_airvisual/framework/google-adk) - [LangChain](https://composio.dev/toolkits/iqair_airvisual/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/iqair_airvisual/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/iqair_airvisual/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/iqair_airvisual/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Iqair airvisual integration - Using Composio's Tool Router to dynamically load and access Iqair airvisual 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 Iqair airvisual MCP server, and what's possible with it? The Iqair airvisual MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Iqair airvisual account. It provides structured and secure access to rich global air quality data, so your agent can perform actions like retrieving real-time AQI, forecasting pollution, checking historical trends, and ranking cities worldwide by air quality on your behalf. - Real-time city and station air quality: Instantly fetch current air quality and weather data for any supported city or monitoring station, based on precise location or station ID. - Air quality forecasting: Ask your agent to provide air quality forecasts for specific cities, helping you plan activities based on pollution trends. - Historical AQI analysis: Retrieve historical air quality index readings for cities to analyze patterns, spot trends, or track improvements over time. - World AQI rankings: Get live rankings of cities worldwide based on current AQI data, or easily find the most and least polluted cities globally. - Location-based discovery: Let your agent list supported countries, states, and cities, or pinpoint the nearest air quality stations and cities using GPS coordinates or IP address. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `IQAIR_AIRVISUAL_GET_AIR_QUALITY_FORECAST_DATA` | Get Air Quality Forecast Data | Tool to retrieve air quality forecast data for a specified city, state, and country. Use after confirming location details. | | `IQAIR_AIRVISUAL_GET_CITIES` | Get Cities | Tool to list supported cities in a specified state and country. Use when you need to retrieve cities for a given state/country. | | `IQAIR_AIRVISUAL_GET_CITY_AIR_QUALITY` | Get City Air Quality | Tool to retrieve air quality data for a specific city. Use when you need current pollution and weather data by specifying city, state, and country. | | `IQAIR_AIRVISUAL_GET_COUNTRIES` | Get supported countries | Tool to list all supported countries. Use when you need to know which countries are supported by the AirVisual API. | | `IQAIR_AIRVISUAL_GET_HISTORICAL_AQI_DATA` | Get Historical AQI Data | Tool to retrieve historical air quality data for a city. Use after confirming city, state, and country when you need AQI readings over time. | | `IQAIR_AIRVISUAL_GET_NEAREST_CITY_AIR_QUALITY` | Get Nearest City Air Quality | Tool to retrieve air quality data for the nearest city based on latitude/longitude or IP. Use when you have precise location data or want to geolocate an IP for air quality. | | `IQAIR_AIRVISUAL_GET_NEAREST_STATION_AIR_QUALITY` | Get Nearest Station Air Quality | Tool to get nearest station air quality. Use when you have GPS coordinates and need closest station’s AQI. | | `IQAIR_AIRVISUAL_GET_STATES` | Get States | Tool to list supported states in a specified country. Use when you need to retrieve states/provinces for a given country. | | `IQAIR_AIRVISUAL_GET_STATION_BY_ID` | Get Station by ID | Fetches current air quality and weather data for a specific location by station/city/state/country names. Falls back to city-level data if the Stations API requires premium access. Returns current AQI (US and China scales), weather conditions, and geographic location. Use Get Countries, Get States, and Get Cities actions to find valid location names. | | `IQAIR_AIRVISUAL_GET_WORLD_RANKING` | Get World AQI Rankings | Retrieves air quality ranking data. With premium API access, returns a global ranking of cities by AQI. With standard (free) API access, automatically falls back to returning the nearest city's air quality as a single-item ranking list. Use lat/lon coordinates or an IP address to specify location for the fallback behavior. Returns city name, location, and current AQI values (US EPA and Chinese MEP standards). | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Iqair airvisual MCP server is an implementation of the Model Context Protocol that connects your AI agent to Iqair airvisual. It provides structured and secure access so your agent can perform Iqair airvisual 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 Iqair airvisual 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 Iqair airvisual-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: ["iqair_airvisual"], }); 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 Iqair airvisual 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 iqair_airvisual, 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 Iqair airvisual 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: ["iqair_airvisual"], }); 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 iqair_airvisual, 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 Iqair airvisual 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 Iqair airvisual MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/iqair_airvisual/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/iqair_airvisual/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/iqair_airvisual/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/iqair_airvisual/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/iqair_airvisual/framework/codex) - [OpenClaw](https://composio.dev/toolkits/iqair_airvisual/framework/openclaw) - [Hermes](https://composio.dev/toolkits/iqair_airvisual/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/iqair_airvisual/framework/cli) - [Google ADK](https://composio.dev/toolkits/iqair_airvisual/framework/google-adk) - [LangChain](https://composio.dev/toolkits/iqair_airvisual/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/iqair_airvisual/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/iqair_airvisual/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/iqair_airvisual/framework/crew-ai) ## Related Toolkits - [Excel](https://composio.dev/toolkits/excel) - Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. 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It helps streamline how you gather, organize, and analyze responses. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Iqair airvisual MCP? With a standalone Iqair airvisual MCP server, the agents and LLMs can only access a fixed set of Iqair airvisual tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Iqair airvisual 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 Iqair airvisual tools. ### Can I manage the permissions and scopes for Iqair airvisual while using Tool Router? Yes, absolutely. You can configure which Iqair airvisual 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 Iqair airvisual data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)