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.

INSTANT PLUG AND PLAY

Sentinel Hub MCP Server for OpenAI Agents SDKGive OpenAI Agents SDK instant access to 14 tools to Catalog Search, Check Sentinel Hub Status, Generate False Color Evalscript, and more

Name: Sentinel Hub
Availability: InStock
Author: Vinkius

Built by Vinkius GDPR 14 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Sentinel Hub through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

Use with Your AI Agent

Ask AI about this App Connector for OpenAI Agents SDK

Open in ChatGPT Open in Claude Open in Perplexity

The Sentinel Hub app connector for OpenAI Agents SDK is a standout in the Cloud Infrastructure 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

python

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="Sentinel Hub Assistant",
            instructions=(
                "You help users interact with Sentinel Hub. "
                "You have access to 14 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Sentinel Hub"
        )
        print(result.final_output)

asyncio.run(main())

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About Sentinel Hub MCP Server

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

The OpenAI Agents SDK auto-discovers all 14 tools from Sentinel Hub through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Sentinel Hub, another analyzes results, and a third generates reports, all orchestrated through Vinkius.

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

The Sentinel Hub MCP Server exposes 14 tools through the Vinkius. Connect it to OpenAI Agents SDK 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 Sentinel Hub tools available for OpenAI Agents SDK

When OpenAI Agents SDK connects to Sentinel Hub through Vinkius, your AI agent gets direct access to every tool listed below — spanning satellite-imagery, earth-observation, geospatial-data, 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.

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

Connect Sentinel Hub to OpenAI Agents SDK via MCP

Follow these steps to wire Sentinel Hub into OpenAI Agents SDK. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 14 tools from Sentinel Hub

Why Use OpenAI Agents SDK with the Sentinel Hub MCP Server

OpenAI Agents SDK provides unique advantages when paired with Sentinel Hub through the Model Context Protocol.

Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Sentinel Hub + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Sentinel Hub MCP Server delivers measurable value.

Automated workflows: build agents that query Sentinel Hub, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents. one queries Sentinel Hub, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Sentinel Hub tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Sentinel Hub to resolve tickets, look up records, and update statuses without human intervention

Example Prompts for Sentinel Hub in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Sentinel Hub immediately.

"Show me an NDVI vegetation analysis for the Amazon rainforest region."

"Find cloud-free Sentinel-2 imagery over Paris with less than 10% clouds."

"What band combinations can I use for wildfire assessment?"

Troubleshooting Sentinel Hub MCP Server with OpenAI Agents SDK

Common issues when connecting Sentinel Hub to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Sentinel Hub + OpenAI Agents SDK FAQ

Common questions about integrating Sentinel Hub MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.

Can I use multiple MCP servers in one agent?

Yes. Pass a list of MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.

Does the SDK support streaming responses?

Yes. The SDK supports SSE and Streamable HTTP transports, both of which work natively with Vinkius.