Sentinel Hub MCP Server with 14 Tools Ready for AI Agents

Name: Sentinel Hub
Availability: InStock
Author: Vinkius

GDPR Free for Subscribers

Access and process satellite imagery from Sentinel, Landsat, and other Earth observation missions through a powerful cloud API. Unlock 14 tools ready out of the box. Connect this App Connector to instantly empower AI agents like Claude Code, Cursor, or any MCP-compatible client with advanced capabilities.

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What is the Sentinel Hub MCP Server?

The Sentinel Hub MCP Server gives AI agents like Claude, ChatGPT, and Cursor direct access to Sentinel Hub via 14 tools. Access and process satellite imagery from Sentinel, Landsat, and other Earth observation missions through a powerful cloud API. Powered by the Vinkius - no API keys, no infrastructure, connect in under 2 minutes.

Built-in capabilities (14)

catalog_searchcheck_sentinel_hub_statusgenerate_false_color_evalscriptgenerate_ndvi_evalscriptgenerate_true_color_evalscriptget_catalog_collectionget_catalog_itemget_statisticsget_user_infolist_band_combinationslist_catalog_collectionsprocess_imagesearch_by_tilesearch_cloud_free

Tools for your AI Agents to operate Sentinel Hub

Ask your AI agent "Show me an NDVI vegetation analysis for the Amazon rainforest region." and get the answer without opening a single dashboard. With 14 tools connected to real Sentinel Hub data, your agents reason over live information, cross-reference it with other MCP servers, and deliver insights you would spend hours assembling manually.

Works with Claude, ChatGPT, Cursor, and any MCP-compatible client. Powered by the Vinkius - your credentials never touch the AI model, every request is auditable. Connect in under two minutes.

Why teams choose Vinkius

One subscription gives you access to thousands of MCP servers - and you can deploy your own to the Vinkius Edge. Your AI agents only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure and security, zero maintenance.

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The Sentinel Hub App Connector works with every AI agent you already use

…and any MCP-compatible client

Use all 14 Sentinel Hub tools with your AI agents right now

Empower your AI agents to connect to Sentinel Hub and securely perform advanced actions on Vinkius infrastructure. Beyond a simple connection, you gain an advanced AI Gateway that provides complete visibility into agent activity, ensuring maximum governance and optimized token usage.

catalog_search

Specify a collection ID (e.g., "sentinel-2-l2a", "sentinel-1-grd"), a bounding box as [west, south, east, north] coordinates, and a date range. Returns item metadata including geometry, cloud cover, and band information. Search the Sentinel Hub STAC catalog for satellite imagery

check_sentinel_hub_status

Returns the connection status and service URL. Use this to verify your client_id:client_secret credentials are working correctly. Verify Sentinel Hub API connectivity and authentication

generate_false_color_evalscript

In the output, healthy vegetation appears bright red, urban areas appear cyan/grey, and water appears dark blue. This is the standard false-color composite used in remote sensing for vegetation mapping and land cover classification. Generate a false-color evalscript for vegetation emphasis

generate_ndvi_evalscript

The output is color-coded: dark for water/shadow, grey for bare soil, yellow-green for sparse vegetation, and deep green for dense vegetation. Use the returned evalscript with the process_image tool. Generate a ready-to-use NDVI evalscript for vegetation analysis

generate_true_color_evalscript

Use the returned evalscript with the process_image tool to get visually appealing satellite photos of any location on Earth. Generate a true-color RGB evalscript for natural imagery

get_catalog_collection

Get detailed information about a specific data collection

get_catalog_item

Use the item ID returned from a catalog_search query. Get detailed metadata for a specific STAC catalog item

get_statistics

Requires an evalscript that defines which bands to analyze. Supports temporal aggregation (daily, weekly, monthly) for time-series analysis of vegetation indices, water levels, or urban expansion. Calculate statistics over an area from satellite imagery

get_user_info

Useful for verifying credentials and understanding available quotas. Get authenticated Sentinel Hub user profile information

list_band_combinations

Includes True Color, False Color (vegetation), NDVI, NDWI, Moisture Index, SWIR, SAR polarizations, Scene Classification, and Burn Severity (NBR). Each entry specifies the required bands and target collection. List predefined satellite band combinations and indices

list_catalog_collections

Includes Sentinel-1 GRD (radar), Sentinel-2 L1C/L2A (optical), Sentinel-3 OLCI/SLSTR, Sentinel-5P (atmosphere), Landsat 8-9, DEM, and Copernicus Land Monitoring Service data. List all available Sentinel Hub satellite data collections

process_image

Specify the data collection, area of interest as a bounding box, date range, and the evalscript. The evalscript defines band inputs, processing logic, and output format. Use generate_ndvi_evalscript or generate_true_color_evalscript tools to get ready-made evalscripts. Process satellite imagery with a custom evalscript

search_by_tile

MGRS tiles are the standard spatial reference for Sentinel-2 data (e.g., "33UUP" for central Europe, "29SQB" for Lisbon area). Returns all scenes for the specified tile within the date range. Search Sentinel-2 imagery by MGRS tile identifier

search_cloud_free

Essential for optical analysis where cloud contamination would corrupt results. Typical thresholds: <10% for clean analysis, <30% for general use, <50% for temporal coverage. Search for cloud-free satellite imagery below a threshold

What the Sentinel Hub MCP Server unlocks

Connect to Sentinel Hub — the most powerful satellite imagery processing API in Europe — and transform raw Earth observation data into actionable intelligence.

What you can do

STAC Catalog Search — Discover available satellite scenes by location, date, collection, cloud cover, and MGRS tile ID across all Sentinel missions and Landsat
Image Processing — Render custom satellite imagery using evalscripts (JavaScript-based processing scripts) that define how bands are combined, indices are calculated, and pixels are colored
Vegetation Analysis (NDVI) — Generate ready-to-use NDVI evalscripts that color-code vegetation density from bare soil to dense forest
Statistical Analysis — Calculate mean, min, max, standard deviation, and histograms over areas of interest with temporal aggregation (daily, weekly, monthly)
Cloud-Free Search — Find satellite scenes below a specified cloud cover threshold for clean optical analysis
Band Combinations — Access a curated library of 10 predefined band combinations including True Color, False Color, NDWI, Moisture Index, SWIR, and Burn Severity

How it works

1. Subscribe to this server
2. Register at dataspace.copernicus.eu and create an OAuth2 client
3. Enter your credentials as client_id:client_secret
4. Start processing satellite imagery from Claude, Cursor, or any MCP-compatible client

Who is this for?

GIS Professionals — process satellite imagery on-demand without downloading terabytes of raw data
Environmental Scientists — compute vegetation, water, and moisture indices for monitoring ecosystems
Urban Planners — analyze land use changes with multi-temporal statistical analysis
Agricultural Advisors — monitor crop health with NDVI time series and cloud-free imagery selection
Emergency Managers — assess wildfire damage with burn severity indices in near real-time

Frequently asked questions about the Sentinel Hub MCP Server

What is an evalscript and how do I use one?

An evalscript is a small JavaScript program that tells Sentinel Hub how to process satellite bands into an output image. It defines which bands to use, how to combine them, and what colors to assign. You can use the generate_ndvi_evalscript or generate_true_color_evalscript tools to get ready-made evalscripts, then pass them to the process_image tool.

Can I analyze vegetation health with this server?

Absolutely. Generate an NDVI evalscript with the generate_ndvi_evalscript tool, then process imagery for your area of interest with the process_image tool. For time-series analysis, use the get_statistics tool with temporal aggregation to track vegetation changes over weeks or months. The search_cloud_free tool helps you find clean scenes without cloud contamination.

What is the difference between this server and the Copernicus Data Space server?

The Copernicus Data Space server focuses on product catalogue search and download — finding and retrieving raw satellite data files. Sentinel Hub focuses on on-the-fly processing — rendering images, computing indices, and generating statistics without downloading raw data. They complement each other: use Copernicus for data discovery and bulk download, Sentinel Hub for real-time analysis and visualization.