IQAir MCP Server for LlamaIndex 6 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add IQAir as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to IQAir. "
"You have 6 tools available."
),
)
response = await agent.run(
"What tools are available in IQAir?"
)
print(response)
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.
LlamaIndex agents combine IQAir tool responses with indexed documents for comprehensive, grounded answers. Connect 6 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the IQAir MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 6 tools from IQAir
Why Use LlamaIndex with the IQAir MCP Server
LlamaIndex provides unique advantages when paired with IQAir through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine IQAir tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain IQAir tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query IQAir, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what IQAir tools were called, what data was returned, and how it influenced the final answer
IQAir + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the IQAir MCP Server delivers measurable value.
Hybrid search: combine IQAir real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query IQAir to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying IQAir for fresh data
Analytical workflows: chain IQAir queries with LlamaIndex's data connectors to build multi-source analytical reports
IQAir MCP Tools for LlamaIndex (6)
These 6 tools become available when you connect IQAir to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting IQAir to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpIQAir + LlamaIndex FAQ
Common questions about integrating IQAir MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
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 LlamaIndex
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.