How to Use the EOSDA Agriculture Satellite Data MCP in Pydantic AI

Enforce strict type validation on satellite telemetry and crop metrics using Pydantic AI.

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Connect EOSDA Agriculture Satellite Data MCP to Pydantic AI

Create your Vinkius account to connect EOSDA Agriculture Satellite Data to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup EOSDA Agriculture Satellite Data with Pydantic AI

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Claude

Perplexity

Type-Safe Vegetation Analysis

Agricultural APIs are notorious for returning messy JSON. When your agent calls this MCP Server via `create_vegetation_task`, Pydantic AI validates the geometry and date ranges before the request even leaves your server. If the satellite returns an unexpected status code in `get_task_result`, the framework throws a validation error immediately. You never end up with hallucinated GeoTIFF URLs corrupting your database.

Strict Scene Metadata Extraction

Finding cloud-free imagery requires exact coordinate matching. Your agent executes `search_dataset` to pull scene IDs, and Pydantic ensures the cloud cover percentages are actually floats. You chain this with `search_multi_dataset` to cross-reference multiple sensors. The framework guarantees that the resulting scene list matches your exact schema, regardless of which LLM you use under the hood.

Discover EOSDA MCP Server Capabilities

Hardcoding index types is a great way to break production code. Your agent dynamically queries `get_available_indices` to build a validated list of supported calculations at runtime. It does the same for sensors using `get_available_datasets`. If a new satellite comes online, your agent knows about it instantly and validates the new string literal without a code deploy.

Setup guide

Set up EOSDA Agriculture Satellite Data MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "eosda-agriculture-satellite-data-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to EOSDA Agriculture Satellite Data tools.",
)

result = await agent.run("List recent EOSDA Agriculture Satellite Data transactions")
print(result.output)

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Common questions about EOSDA Agriculture Satellite Data MCP in Pydantic AI

Install the slim package with MCP support. Initialize an MCPToolset with your HTTP endpoint and pass it directly to your agent's toolsets array.

Pydantic AI catches it instantly. The framework throws a runtime error instead of letting your agent hallucinate a valid response based on broken geographic coordinates.

You write the loop, but Pydantic validates the state. The agent checks the task status, and if the API structure changes mid-poll, the framework stops execution.

Yes. Because Pydantic AI is model-agnostic, you can use a local Llama instance to parse the satellite metadata, provided the model is smart enough to format the tool calls correctly.

Validation prevents malformed requests from leaking unintended data. However, the exact GeoJSON boundaries and task parameters are still transmitted to the external satellite provider for processing.

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