IQAir MCP Server for LangChain 6 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect IQAir through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"iqair": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using IQAir, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About IQAir MCP Server
Empower your AI agent to orchestrate your entire environmental research and air quality auditing workflow with IQAir, the world's most popular platform for air quality data. By connecting the AirVisual API to your agent, you transform complex pollution searches into a natural conversation. Your agent can instantly retrieve real-time air quality indices (AQI), audit weather conditions, and identify the most polluted areas without you ever touching a technical portal. Whether you are conducting climate research or monitoring local health constraints, your agent acts as a real-time environmental assistant, ensuring your data is always precise and localized.
LangChain's ecosystem of 500+ components combines seamlessly with IQAir through native MCP adapters. Connect 6 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
What you can do
- Pollution Auditing — Retrieve real-time Air Quality Index (AQI) data for the nearest city or specific global locations instantly.
- Weather Oversight — Audit current weather conditions, including temperature, humidity, and atmospheric pressure, to maintain a clear view of environmental scale.
- Geographic Discovery — List all supported countries, states, and cities in the IQAir catalog to understand the geographic reach of air quality monitoring.
- Local Intelligence — Query specific city data to understand local pollution markers and main pollutants (e.g., p2, p1).
- Operational Monitoring — Check API status to ensure your environmental research workflow is always operational.
The IQAir MCP Server exposes 6 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect IQAir to LangChain via MCP
Follow these steps to integrate the IQAir MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 6 tools from IQAir via MCP
Why Use LangChain with the IQAir MCP Server
LangChain provides unique advantages when paired with IQAir through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine IQAir MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across IQAir queries for multi-turn workflows
IQAir + LangChain Use Cases
Practical scenarios where LangChain combined with the IQAir MCP Server delivers measurable value.
RAG with live data: combine IQAir tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query IQAir, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain IQAir tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every IQAir tool call, measure latency, and optimize your agent's performance
IQAir MCP Tools for LangChain (6)
These 6 tools become available when you connect IQAir to LangChain via MCP:
check_api_status
Check if the IQAir API is operational
get_city_air_quality
Get real-time air quality and weather for a specific city
get_nearest_city_air_quality
Get real-time air quality and weather for the city nearest to the requester IP
list_supported_cities
List all cities supported for a specific state and country
list_supported_countries
List all countries supported by IQAir
list_supported_states
List all states supported for a specific country
Example Prompts for IQAir in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with IQAir immediately.
"What is the air quality in 'Los Angeles, California, USA' using IQAir?"
"Check air quality for my nearest city."
"List all cities supported in the state of 'Sao Paulo', Brazil."
Troubleshooting IQAir MCP Server with LangChain
Common issues when connecting IQAir to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersIQAir + LangChain FAQ
Common questions about integrating IQAir MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
Connect IQAir with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect IQAir to LangChain
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.