What satellites are covered by this integration?

The server provides access to Sentinel-2 (high resolution), Sentinel-1 (radar), Landsat 8 and 9 (historical and medium res), and MODIS (high temporal resolution).

How do I calculate the NDVI for a specific field?

Use the `create_vegetation_task` tool. You need to provide the `index_type` as 'NDVI', the `dataset_id` (e.g., 'sentinel2'), and the `aoi` (Area of Interest) coordinates in GeoJSON format.

Is the area of interest (AOI) required for searches?

For general searches, it is optional but highly recommended to narrow down results. For index calculation tasks (`create_vegetation_task`), the AOI is mandatory to define the target area.

EOSDA Agriculture Satellite Data MCP Server for Google ADK 6 tools — connect in under 2 minutes

Name: EOSDA Agriculture Satellite Data
Availability: InStock
Author: Vinkius

google.github.io/adk-docs/tools/mcp-tools

Built by Vinkius GDPR 6 Tools SDK

Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add EOSDA Agriculture Satellite Data as an MCP tool provider through the Vinkius and your ADK agents can call every tool with full schema introspection.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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Vinkius supports streamable HTTP and SSE.

python

from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
    StreamableHTTPConnectionParams,
)

# Your Vinkius token — get it at cloud.vinkius.com
mcp_tools = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    )
)

agent = Agent(
    model="gemini-2.5-pro",
    name="eosda_agriculture_satellite_data_agent",
    instruction=(
        "You help users interact with EOSDA Agriculture Satellite Data "
        "using 6 available tools."
    ),
    tools=[mcp_tools],
)

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About EOSDA Agriculture Satellite Data MCP Server

Empower your AI agent with cutting-edge remote sensing capabilities via the EOSDA Agriculture MCP server. This integration provides instant access to high-resolution satellite data from Sentinel and Landsat missions, specifically processed for precision farming. Your agent can search for imagery across global datasets, calculate vegetation indices like NDVI, EVI, and MSAVI, and monitor soil moisture trends over time. Whether you are optimizing fertilizer application, auditing crop health, or monitoring land use, your agent acts as a dedicated agronomist and remote sensing specialist through natural conversation.

Google ADK natively supports EOSDA Agriculture Satellite Data as an MCP tool provider — declare the Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 6 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.

What you can do

Satellite Imagery Search — Search Sentinel-2, Landsat 8/9, and MODIS datasets by date and area of interest.
Vegetation Indices — Trigger processing tasks for NDVI (health), EVI (biomass), and other critical indices.
Health Monitoring — Retrieve processed results to identify areas of stress or high productivity in fields.
Dataset Intelligence — Access technical specs for available satellites including resolution and revisit times.
AOI Analysis — Input GeoJSON areas of interest to get localized intelligence for specific farms or regions.

The EOSDA Agriculture Satellite Data MCP Server exposes 6 tools through the Vinkius. Connect it to Google ADK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect EOSDA Agriculture Satellite Data to Google ADK via MCP

Follow these steps to integrate the EOSDA Agriculture Satellite Data MCP Server with Google ADK.

Install Google ADK

Run pip install google-adk

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Create the agent

Save the code above and integrate into your ADK workflow

Explore tools

The agent will discover 6 tools from EOSDA Agriculture Satellite Data via MCP

Why Use Google ADK with the EOSDA Agriculture Satellite Data MCP Server

Google ADK provides unique advantages when paired with EOSDA Agriculture Satellite Data through the Model Context Protocol.

Google ADK natively supports MCP tool servers — declare a tool provider and the framework handles discovery, validation, and execution

Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with EOSDA Agriculture Satellite Data

Production-ready features like session management, evaluation, and deployment come built-in — not bolted on

Seamless integration with Google Cloud services means you can combine EOSDA Agriculture Satellite Data tools with BigQuery, Vertex AI, and Cloud Functions

EOSDA Agriculture Satellite Data + Google ADK Use Cases

Practical scenarios where Google ADK combined with the EOSDA Agriculture Satellite Data MCP Server delivers measurable value.

Enterprise data agents: ADK agents query EOSDA Agriculture Satellite Data and cross-reference results with internal databases for comprehensive analysis

Multi-modal workflows: combine EOSDA Agriculture Satellite Data tool responses with Gemini's vision and language capabilities in a single agent

Automated compliance checks: schedule ADK agents to query EOSDA Agriculture Satellite Data regularly and flag policy violations or configuration drift

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including EOSDA Agriculture Satellite Data

EOSDA Agriculture Satellite Data MCP Tools for Google ADK (6)

These 6 tools become available when you connect EOSDA Agriculture Satellite Data to Google ADK via MCP:

create_vegetation_task

) for a specific area of interest. Returns a task ID that can be used with get_task_result to retrieve results. Use get_available_indices to see all available index types. Create a vegetation index calculation task (NDVI, EVI, etc.)

get_available_datasets

Use these dataset IDs for search_dataset and create_vegetation_task. Get list of available satellite datasets

get_available_indices

Use these index types with create_vegetation_task. Get list of available vegetation indices

get_task_result

Returns the processed vegetation index data, download URLs and status. Get the result of a vegetation index task

search_dataset

) within a date range and optional area of interest. Returns scene IDs, dates, cloud cover percentages and download URLs. Use get_available_datasets to see all dataset options. Search satellite imagery for a specific dataset

search_multi_dataset

g. Sentinel-2 and Landsat 8 together). Returns scenes from all requested datasets within the date range and area of interest. Search satellite imagery across multiple datasets

Example Prompts for EOSDA Agriculture Satellite Data in Google ADK

Ready-to-use prompts you can give your Google ADK agent to start working with EOSDA Agriculture Satellite Data immediately.

"Find Sentinel-2 images for my farm from the last month."

"Calculate the NDVI for this area: [GeoJSON coords]."

"What is the resolution of Landsat 8 satellite data?"

Troubleshooting EOSDA Agriculture Satellite Data MCP Server with Google ADK

Common issues when connecting EOSDA Agriculture Satellite Data to Google ADK through the Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

EOSDA Agriculture Satellite Data + Google ADK FAQ

Common questions about integrating EOSDA Agriculture Satellite Data MCP Server with Google ADK.

How does Google ADK connect to MCP servers?

Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.

Can ADK agents use multiple MCP servers?

Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.

Which Gemini models work best with MCP tools?

Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.