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Copernicus Data Space MCP Server for Mastra AIGive Mastra AI instant access to 14 tools to Check Copernicus Status, Count Products, Get Collection, and more

Built by Vinkius GDPR 14 Tools SDK

Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect Copernicus Data Space through Vinkius and Mastra agents discover all tools automatically. type-safe, streaming-ready, and deployable anywhere Node.js runs.

Ask AI about this App Connector for Mastra AI

The Copernicus Data Space app connector for Mastra AI is a standout in the The Unthinkable category — giving your AI agent 14 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

typescript
import { Agent } from "@mastra/core/agent";
import { createMCPClient } from "@mastra/mcp";
import { openai } from "@ai-sdk/openai";

async function main() {
  // Your Vinkius token. get it at cloud.vinkius.com
  const mcpClient = await createMCPClient({
    servers: {
      "copernicus-data-space": {
        url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
      },
    },
  });

  const tools = await mcpClient.getTools();
  const agent = new Agent({
    name: "Copernicus Data Space Agent",
    instructions:
      "You help users interact with Copernicus Data Space " +
      "using 14 tools.",
    model: openai("gpt-4o"),
    tools,
  });

  const result = await agent.generate(
    "What can I do with Copernicus Data Space?"
  );
  console.log(result.text);
}

main();
Copernicus Data Space
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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Copernicus Data Space MCP Server

Connect to the Copernicus Data Space Ecosystem and unlock the world's largest open Earth observation archive directly from your AI agent.

Mastra's agent abstraction provides a clean separation between LLM logic and Copernicus Data Space tool infrastructure. Connect 14 tools through Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution. deployable to any Node.js host in one command.

What you can do

  • Product Discovery — Search across Sentinel-1 (radar), Sentinel-2 (optical), Sentinel-3 (ocean/land), Sentinel-5P (atmosphere), and Sentinel-6 (altimetry) collections with temporal, spatial, and attribute filters
  • Geographic Search — Find satellite products covering any location on Earth using bounding box coordinates or WKT polygon geometries
  • Orbit-Based Queries — Retrieve data from specific satellite orbits for interferometry, change detection, and repeat-pass analysis
  • Product Inspection — Access complete metadata, quicklook previews, and internal file structure for any product
  • Download Orchestration — Generate authenticated download URLs with time-limited Bearer tokens for direct product retrieval
  • Data Volume Assessment — Count products matching your criteria before executing full searches

The Copernicus Data Space MCP Server exposes 14 tools through the Vinkius. Connect it to Mastra AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 14 Copernicus Data Space tools available for Mastra AI

When Mastra AI connects to Copernicus Data Space through Vinkius, your AI agent gets direct access to every tool listed below — spanning satellite-imagery, geospatial-analysis, earth-observation, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

check_copernicus_status

Returns the connection status. Use this to verify your client_id:client_secret credentials are working correctly. Verify Copernicus Data Space API connectivity and authentication

count_products

Useful for understanding data volume before executing a full search, or for monitoring data availability trends. Count total products available for a collection and date range

get_collection

Use collection names like "SENTINEL-2", "SENTINEL-1", or "SENTINEL-3". Get details about a specific Copernicus collection

get_product

Returns name, sensing time, footprint geometry, file size, checksum, and all associated attributes. Use this after searching to inspect a specific product before downloading. Get detailed metadata for a specific satellite product by UUID

get_product_download_url

Returns the direct download URL along with a Bearer token valid for approximately one hour. Use this to download raw satellite data products (typically in SAFE format for Sentinel data). Generate an authenticated download URL for a product

get_quicklook

Useful for understanding the product structure and accessing thumbnail previews without downloading the full product. Get quicklook preview and file nodes for a product

list_attributes

This helps you understand what filtering parameters are available (e.g., cloud cover percentage, orbit direction, processing level) for refining product searches. List available metadata attributes for a collection

list_collections

Includes Sentinel-1 (radar), Sentinel-2 (optical), Sentinel-3 (ocean/land), Sentinel-5P (atmosphere), Sentinel-6 (altimetry), and complementary missions like Landsat. Each entry includes temporal coverage and description. List all available Copernicus satellite data collections

list_latest_products

Useful for monitoring new data availability or checking processing pipeline status. List the most recently published satellite products

list_product_nodes

Returns the hierarchy of files including measurement data, metadata XML, quicklook images, and auxiliary data. Essential for understanding product structure before selective download. List all files contained within a satellite product

search_by_bbox

Combines spatial filtering with collection and temporal constraints. Ideal for region-specific analysis workflows. Search satellite products within a geographic bounding box

search_by_name

Useful for finding specific orbits, tiles (e.g., "T33UUP" for Sentinel-2 tile), or granule identifiers. Returns product metadata ordered by sensing date. Search satellite products by name pattern

search_by_orbit_number

Especially useful for Sentinel-1 (SAR) and Sentinel-2 (optical) repeat-pass analysis, interferometry, and change detection workflows where you need data from the exact same orbit geometry. Search satellite products by orbit number

search_products

Specify a collection name (e.g., "SENTINEL-2", "SENTINEL-1"), a date range in YYYY-MM-DD format, and optionally an area of interest as a WKT polygon. Returns product metadata including name, footprint, size, and publication date. Maximum 20 results by default. Search Sentinel satellite products by collection, date range, and area

Connect Copernicus Data Space to Mastra AI via MCP

Follow these steps to wire Copernicus Data Space into Mastra AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install dependencies

Run npm install @mastra/core @mastra/mcp @ai-sdk/openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.ts and run with npx tsx agent.ts
04

Explore tools

Mastra discovers 14 tools from Copernicus Data Space via MCP

Why Use Mastra AI with the Copernicus Data Space MCP Server

Mastra AI provides unique advantages when paired with Copernicus Data Space through the Model Context Protocol.

01

Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure. add Copernicus Data Space without touching business code

02

Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation

03

TypeScript-native: full type inference for every Copernicus Data Space tool response with IDE autocomplete and compile-time checks

04

One-command deployment to any Node.js host. Vercel, Railway, Fly.io, or your own infrastructure

Copernicus Data Space + Mastra AI Use Cases

Practical scenarios where Mastra AI combined with the Copernicus Data Space MCP Server delivers measurable value.

01

Automated workflows: build multi-step agents that query Copernicus Data Space, process results, and trigger downstream actions in a typed pipeline

02

SaaS integrations: embed Copernicus Data Space as a first-class tool in your product's AI features with Mastra's clean agent API

03

Background jobs: schedule Mastra agents to query Copernicus Data Space on a cron and store results in your database automatically

04

Multi-agent systems: create specialist agents that collaborate using Copernicus Data Space tools alongside other MCP servers

Example Prompts for Copernicus Data Space in Mastra AI

Ready-to-use prompts you can give your Mastra AI agent to start working with Copernicus Data Space immediately.

01

"Find Sentinel-2 satellite images over Lisbon from the last week."

02

"How many Sentinel-1 radar products are available for January 2026?"

03

"What data collections are available in the Copernicus Data Space?"

Troubleshooting Copernicus Data Space MCP Server with Mastra AI

Common issues when connecting Copernicus Data Space to Mastra AI through the Vinkius, and how to resolve them.

01

createMCPClient not exported

Install: npm install @mastra/mcp

Copernicus Data Space + Mastra AI FAQ

Common questions about integrating Copernicus Data Space MCP Server with Mastra AI.

01

How does Mastra AI connect to MCP servers?

Create an MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.
02

Can Mastra agents use tools from multiple servers?

Yes. Pass multiple MCP clients to the agent constructor. Mastra merges all tool schemas and the agent can call any tool from any server.
03

Does Mastra support workflow orchestration?

Yes. Mastra has a built-in workflow engine that lets you chain MCP tool calls with branching logic, error handling, and parallel execution.