How to Use the PurpleAir MCP in LlamaIndex

Q: Does LlamaIndex support querying the PurpleAir MCP Server directly?

Yes. You can configure your agent to use tools like getsensorsnearme as part of its retrieval strategy. It pulls the data, indexes it, and provides an answer.

Turn real-time atmospheric data into searchable knowledge with LlamaIndex and the PurpleAir MCP Server.

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Connect PurpleAir MCP to LlamaIndex

Create your Vinkius account to connect PurpleAir to LlamaIndex — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup PurpleAir with LlamaIndex

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Index live air quality data

Convert raw readings from `get_sensor_data` into structured knowledge for your RAG applications. LlamaIndex ingests these outputs to build a searchable index of current conditions. This makes your historical and real-time data queryable via natural language. You stop guessing and start getting answers grounded in actual sensor metrics.

Query past sensor conditions

Use `get_sensor_history_csv` to pull logs and add them to your knowledge base. LlamaIndex then parses these logs to answer questions about past pollution events. It turns flat files into an intelligent resource. You gain the ability to search across time-series data without writing complex database queries manually.

Map sensor networks spatially

Fetch geographic sensor data using `get_sensors_by_bounding_box` and index the locations. LlamaIndex links these coordinates to your existing documents for location-aware retrieval. You can ask about air quality in specific urban areas and get results based on the nearest indexed sensors. It bridges the gap between static documents and live hardware data.

Setup guide

Set up PurpleAir 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 PurpleAir 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 PurpleAir tools.",
)
response = await agent.run("List recent PurpleAir data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by PurpleAir. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about PurpleAir MCP in LlamaIndex

Use the BasicMCPClient to connect the server, then convert the tools into an McpToolSpec. Once the tools are available to your FunctionAgent, you can index the results of your queries.

Yes. You can configure your agent to use tools like `get_sensors_near_me` as part of its retrieval strategy. It pulls the data, indexes it, and provides an answer.

It works perfectly for grounding. By fetching current readings before generating a response, the agent provides answers based on the latest available air quality data.

It is. You can use the async tool list generation to ensure your LlamaIndex application remains responsive while fetching sensor data.

Only public sensor readings and metadata are accessed. Your API key and specific query history remain isolated within your local environment and the ephemeral Vinkius sandbox.

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