OpenAQ MCP Server for LlamaIndex 9 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add OpenAQ as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
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 OpenAQ. "
"You have 9 tools available."
),
)
response = await agent.run(
"What tools are available in OpenAQ?"
)
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 OpenAQ MCP Server
Connect OpenAQ, the world's largest open air quality database, to any AI agent and monitor real-time pollution levels, track air quality trends, and access data from thousands of monitoring stations globally through natural language.
LlamaIndex agents combine OpenAQ tool responses with indexed documents for comprehensive, grounded answers. Connect 9 tools through the 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
- Live Monitoring — Get the latest PM2.5, O3, NO2, SO2, and CO readings from any location worldwide
- Historical Analysis — Query time-series measurement data with date range filters for trend analysis
- Location Discovery — Browse monitoring stations by country, city, or geographic area
- Sensor Tracking — View active sensor devices and their measurement parameters
- Parameter Reference — Look up all measurable air quality parameters with units and classifications
- Global Coverage — Access data from 100+ countries with thousands of active monitoring locations
The OpenAQ MCP Server exposes 9 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 OpenAQ to LlamaIndex via MCP
Follow these steps to integrate the OpenAQ 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 9 tools from OpenAQ
Why Use LlamaIndex with the OpenAQ MCP Server
LlamaIndex provides unique advantages when paired with OpenAQ through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine OpenAQ tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain OpenAQ tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query OpenAQ, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what OpenAQ tools were called, what data was returned, and how it influenced the final answer
OpenAQ + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the OpenAQ MCP Server delivers measurable value.
Hybrid search: combine OpenAQ real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query OpenAQ 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 OpenAQ for fresh data
Analytical workflows: chain OpenAQ queries with LlamaIndex's data connectors to build multi-source analytical reports
OpenAQ MCP Tools for LlamaIndex (9)
These 9 tools become available when you connect OpenAQ to LlamaIndex via MCP:
get_countries
Includes location counts and city counts per country. List countries with monitoring stations
get_latest_measurements
Useful for getting current air quality status without querying full history. Get latest measurements per location
get_location_by_id
Get details for a specific location
get_locations
Filter by country, city, parameter, or geographic bounding box. Returns location details including coordinates, sensor counts, and whether the station is an official monitor. List air quality monitoring locations
get_measurements
Filter by location, parameter, date range, and value range. Returns readings with timestamps. Get historical air quality measurements
get_parameter_by_id
Get details for a specific parameter
get_parameters
5, PM10, O3 (ozone), NO2, SO2, CO, etc. Includes units and whether each is a core parameter. List measurable air quality parameters
get_sensor_by_id
Get details for a specific sensor
get_sensors
Filter by location, parameter type, or active status. List air quality sensors
Example Prompts for OpenAQ in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with OpenAQ immediately.
"What's the current PM2.5 level in São Paulo, Brazil?"
"Which countries have the most air quality monitoring stations?"
"Show me ozone (O3) measurements from the last 24 hours in Paris."
Troubleshooting OpenAQ MCP Server with LlamaIndex
Common issues when connecting OpenAQ to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpOpenAQ + LlamaIndex FAQ
Common questions about integrating OpenAQ 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 OpenAQ 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 OpenAQ to LlamaIndex
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.