How to Use the Copernicus Data Space MCP in CrewAI

Q: Can a CrewAI agent verify Copernicus Data Space status?

Yes, include checkcopernicusstatus in your agent's tool set. It can run this check at the start of every shift.

Deploy a crew of autonomous agents to analyze Copernicus Data Space imagery with CrewAI.

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Connect Copernicus Data Space MCP to CrewAI

Create your Vinkius account to connect Copernicus Data Space 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 Copernicus Data Space with CrewAI

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Perplexity

Collaborative satellite research in CrewAI

One agent searches with `search_products` while another agent uses `list_product_nodes` to inspect the file structure. They share memory to ensure the analysis agent has the right file list before starting. This keeps the research phase organized. You don't have to manage the handoff between the discovery and inspection steps.

Autonomous region monitoring with CrewAI

Set a monitor agent to run `search_by_bbox` on a loop. When it finds new imagery, it alerts the analysis agent to inspect the quicklooks using `get_quicklook`. Your crew handles the entire operation. It filters for new data and triggers alerts only when specific geographic criteria are met.

Precise metadata filtering for CrewAI crews

Use `list_attributes` to teach your agents what parameters they can filter by. They then build complex queries for `search_products` that include cloud cover and orbit direction. This specialization makes your agents smarter. They know exactly how to query the satellite archives to get the most relevant data for your project.

Setup guide

Set up Copernicus Data Space 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 Copernicus Data Space tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Copernicus Data Space 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 Copernicus Data Space. 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 Copernicus Data Space MCP in CrewAI

Add the server URL to your agent's MCP configuration. You can then filter the tools to give specific agents access to specific Copernicus functions.

Yes, they share memory. One agent can find a product UUID and pass it to another agent to run `get_product_download_url`.

You control which agents have access to which tools. You can limit the search tools to a single research agent.

Yes, include `check_copernicus_status` in your agent's tool set. It can run this check at the start of every shift.

The server only processes metadata queries. No raw satellite data is stored on our infrastructure, keeping your usage private.

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