How to Use the Emissions API MCP in CrewAI

Deploy specialized agent teams to audit global pollution with CrewAI and the Emissions API.

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Connect Emissions API MCP to CrewAI

Create your Vinkius account to connect Emissions API 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 Emissions API with CrewAI

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Coordinate Multi-Agent Gas Audits

The Emissions API MCP Server exposes `get_nitrogen_dioxide` to feed precise atmospheric data directly to your specialized CrewAI agents. You can assign an Analyst Agent to monitor nitrogen levels while a Writer Agent drafts environmental compliance reports based on the findings. CrewAI manages the shared memory between these agents, allowing them to pass spatial context back and forth. When the Analyst Agent calls `get_carbon_monoxide`, the Moderator Agent can immediately review the reading and trigger an escalation protocol if safety limits are breached.

Spatial Analysis with Hierarchical Agent Crews

The Emissions API MCP Server lets you deploy hierarchical agent structures to process complex spatial datasets. A manager agent coordinates the workflow, instructing a spatial specialist agent to call `get_geojson_emissions` to extract localized pollution boundaries. The spatial data is then passed to a researcher agent who queries `get_methane` to match gas concentrations with specific coordinates. This collaboration happens autonomously, allowing you to run continuous air quality audits without manual intervention.

Autonomous Ozone Monitoring with the CrewAI MCP Server

Tracking global ozone layers requires continuous background monitoring, which you can automate by exposing `get_ozone` to a dedicated CrewAI team. The agents run in the background, checking gas levels against historical baselines and collaborating to identify anomalies. Your crew begins by calling `get_available_products` to verify active data pipelines. Once verified, the agents distribute tasks—one querying ozone data while another maps the results—ensuring your environmental monitoring pipeline runs with zero human friction.

Setup guide

Set up Emissions API 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 Emissions API tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Emissions API 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="Emissions API Analyst",
        goal="Access and analyze Emissions API data via MCP.",
        backstory="Expert analyst with direct Emissions API access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Emissions API 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 Emissions API. 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 Emissions API MCP in CrewAI

You pass the MCP server URL directly in your CrewAI agent configuration. This makes tools like `get_nitrogen_dioxide` and `get_methane` available to any specialized agent in your crew, enabling collaborative data analysis.

Yes, you can configure your crew for hierarchical or sequential execution. One agent can call `get_carbon_monoxide` while another queries `get_ozone` simultaneously, merging their findings in shared memory.

Yes, you can use the advanced setup with MCPServerHTTP and a tool filter. This allows you to restrict certain agents to only `get_available_products` while letting your analyst agents access the spatial tool `get_geojson_emissions`.

If a query returns empty results, your agents can use their shared memory and reasoning capabilities to pivot. For example, if `get_methane` has no recent data, the agent can automatically query `get_carbon_monoxide` to look for alternative industrial indicators.

All atmospheric gas metrics, GeoJSON polygons, and product catalogs queried by your agents are processed in an isolated sandbox. The raw environmental data remains in-transit only, with zero persistent storage of your geographical coordinates on Vinkius.

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