Copernicus Data Space MCP Server for LlamaIndexGive LlamaIndex instant access to 14 tools to Check Copernicus Status, Count Products, Get Collection, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Copernicus Data Space as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this App Connector for LlamaIndex
The Copernicus Data Space app connector for LlamaIndex 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
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Copernicus Data Space. "
"You have 14 tools available."
),
)
response = await agent.run(
"What tools are available in Copernicus Data Space?"
)
print(response)
asyncio.run(main())
* 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.
LlamaIndex agents combine Copernicus Data Space tool responses with indexed documents for comprehensive, grounded answers. Connect 14 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex
When LlamaIndex 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.
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
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
Use collection names like "SENTINEL-2", "SENTINEL-1", or "SENTINEL-3". Get details about a specific Copernicus collection
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
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
Useful for understanding the product structure and accessing thumbnail previews without downloading the full product. Get quicklook preview and file nodes for a product
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
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
Useful for monitoring new data availability or checking processing pipeline status. List the most recently published satellite products
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
Combines spatial filtering with collection and temporal constraints. Ideal for region-specific analysis workflows. Search satellite products within a geographic bounding box
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
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
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 LlamaIndex via MCP
Follow these steps to wire Copernicus Data Space into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Copernicus Data Space MCP Server
LlamaIndex provides unique advantages when paired with Copernicus Data Space through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Copernicus Data Space tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Copernicus Data Space tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Copernicus Data Space, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Copernicus Data Space tools were called, what data was returned, and how it influenced the final answer
Copernicus Data Space + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Copernicus Data Space MCP Server delivers measurable value.
Hybrid search: combine Copernicus Data Space real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Copernicus Data Space to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Copernicus Data Space for fresh data
Analytical workflows: chain Copernicus Data Space queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Copernicus Data Space in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Copernicus Data Space immediately.
"Find Sentinel-2 satellite images over Lisbon from the last week."
"How many Sentinel-1 radar products are available for January 2026?"
"What data collections are available in the Copernicus Data Space?"
Troubleshooting Copernicus Data Space MCP Server with LlamaIndex
Common issues when connecting Copernicus Data Space to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpCopernicus Data Space + LlamaIndex FAQ
Common questions about integrating Copernicus Data Space MCP Server with LlamaIndex.