How to Use the Google Air Quality MCP in CrewAI

Q: How do I connect Google Air Quality tools to a CrewAI agent?

You pass the Vinkius URL directly in the agent's mcps parameter during initialization. This instantly exposes both getcurrentairquality and getairqualityhistory to that specific CrewAI agent.

Q: How do I limit which CrewAI agents can access this MCP Server?

Use the MCPServerHTTP class from the crewai.mcp package. This lets you apply a toolfilter, ensuring only your specialized environmental agents can invoke the Google Air Quality tools.

Q: What is the best way to run CrewAI tasks that require historical Google Air Quality data?

Define a sequential crew where the first agent uses getairqualityhistory to gather the raw intervals. The second agent then processes this data to write a detailed environmental report.

Let specialized CrewAI agent teams analyze and act on Google Air Quality data autonomously.

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Connect Google Air Quality MCP to CrewAI

Create your Vinkius account to connect Google Air Quality to CrewAI 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 Google Air Quality with CrewAI

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Multi-Agent Environmental Analysis

The `get_current_air_quality` tool provides real-time Google environmental metrics to your CrewAI agents, enabling coordinated team decisions. A CrewAI researcher agent can pull the raw Google AQI, while a CrewAI analyst agent translates the specific pollutants into actionable advice. You set this up by adding the Google Air Quality server URL directly to the `mcps` array in your CrewAI agent configuration. The CrewAI agents share these Google tools across their shared memory, ensuring everyone has the exact same real-time environmental context.

Autonomous Trend Reports with this MCP Server

The `get_air_quality_history` tool lets your CrewAI team compile deep historical reports on Google-tracked pollution without human intervention. Your CrewAI writer agent can request past data from the analyst agent, who uses the Google history tool to extract pollution trends over the last week. This autonomous CrewAI coordination happens in the background. CrewAI manages the sequential execution, passing the historical Google Air Quality JSON payloads between agents until the final markdown report is generated.

Hierarchical Escalation for Severe Pollution Events

This MCP Server enables CrewAI managers to oversee complex safety protocols based on live Google atmospheric data. When the CrewAI monitoring agent detects dangerous Google-reported particulate matter, it escalates the incident to a CrewAI supervisor agent for immediate notification dispatch. For advanced setups, you can use the CrewAI server classes to filter which agents have access to specific Google Air Quality tools. This keeps your specialized CrewAI agents focused on their exact roles without cluttering their context windows with irrelevant Google data.

Setup guide

Set up Google Air Quality MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Google Air Quality tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Google Air Quality Analyst",
    goal="Access and analyze Google Air Quality data via MCP.",
    backstory="Expert analyst with direct Google Air Quality access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Google Air Quality transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Google Air Quality Analyst",
        goal="Access and analyze Google Air Quality data via MCP.",
        backstory="Expert analyst with direct Google Air Quality access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Google Air Quality transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Google Air Quality. 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 Google Air Quality MCP in CrewAI

You pass the Vinkius URL directly in the agent's `mcps` parameter during initialization. This instantly exposes both `get_current_air_quality` and `get_air_quality_history` to that specific CrewAI agent.

Yes, CrewAI agents use shared memory. Once one agent retrieves the current AQI using `get_current_air_quality`, the other agents in the crew can access that data to coordinate their tasks.

Use the `MCPServerHTTP` class from the `crewai.mcp` package. This lets you apply a `tool_filter`, ensuring only your specialized environmental agents can invoke the Google Air Quality tools.

Define a sequential crew where the first agent uses `get_air_quality_history` to gather the raw intervals. The second agent then processes this data to write a detailed environmental report.

The coordinates used for AQI lookups are transmitted through Vinkius's secure, ephemeral V8 sandboxes. CrewAI passes the lat/long pair directly to the Google endpoint, ensuring your spatial data is never logged or stored.

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