How to Use the IQAir MCP in LlamaIndex

Q: Can I index IQAir pollution metrics for semantic search in LlamaIndex?

Yes, you can. Your agent runs getcityairquality, takes the raw JSON payload, and writes it directly to your vector index for immediate querying.

Q: How does LlamaIndex handle geographic filtering with IQAir?

Your agent uses listsupportedcities to verify a location exists before attempting to index it. This keeps your vector store clean and free of empty data nodes.

Index live IQAir environmental metrics directly into your LlamaIndex vector stores for search grounded in real-time air quality data.

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Connect IQAir MCP to LlamaIndex

Create your Vinkius account to connect IQAir to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup IQAir with LlamaIndex

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Index live IQAir data for RAG workflows

The `get_city_air_quality` tool fetches real-time pollution metrics that your LlamaIndex pipeline writes directly to your vector store. Instead of relying on static documents, your RAG setup queries this live index to answer user questions with current data. This prevents your agent from hallucinating old air index numbers. Every query pulls fresh data, indexes it, and matches it against your historical document store.

Build location-aware search indexes with LlamaIndex

The `get_nearest_city_air_quality` tool resolves environmental data based on the user's IP. Your LlamaIndex agent takes this localized output, indexes it, and uses semantic search to find relevant regional health advice in your local database. You don't need to ask the user for their city. The agent handles the lookup, indexes the result, and serves hyper-local answers instantly.

Structure geographic indexes using the IQAir MCP Server

The `list_supported_countries` tool provides the structural hierarchy your LlamaIndex setup needs to categorize environmental documents. Your agent uses this list to tag and organize incoming pollution reports by country. You can drill down further by having the agent call `list_supported_states` and `list_supported_cities` to build a clean, searchable index tree. This keeps your vector store organized and your search results highly relevant.

Setup guide

Set up IQAir MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all IQAir MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to IQAir tools.",
)
response = await agent.run("List recent IQAir data")

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Common questions about IQAir MCP in LlamaIndex

Use the llama-index-tools-mcp package to connect to your Vinkius endpoint. Convert the MCP tools into LlamaIndex tool specs, then pass them to your FunctionAgent.

Yes, you can. Your agent runs `get_city_air_quality`, takes the raw JSON payload, and writes it directly to your vector index for immediate querying.

Your agent uses `list_supported_cities` to verify a location exists before attempting to index it. This keeps your vector store clean and free of empty data nodes.

Running this tool ensures the API is active before your indexing pipeline starts a bulk run. It prevents your agent from indexing empty or failed responses.

The MCP Server processes your IP and state queries inside an isolated V8 sandbox. Your sensitive location data is used solely to fetch the current air index and is destroyed the moment the tool execution finishes.

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