How to Use the INPE (STAC API - Satélites) MCP in Google ADK

Q: How do I integrate INPE (STAC API - Satélites) with Google ADK?

Initialize the McpToolset with the server URL and add it to your LlmAgent. Your agent will then gain access to the six satellite tools.

Q: Can I restrict which tools are exposed to my Google ADK agent?

Yes, use the toolnames filter in the McpToolset configuration. This lets you hide tools you don't need for a specific agent role.

Connect your Google ADK agents to INPE satellite data for large-scale geospatial reasoning.

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Connect INPE (STAC API - Satélites) MCP to Google ADK

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Setup INPE (STAC API - Satélites) with Google ADK

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Explore the INPE catalog

Call `list_collections` to see all imagery sets available on the INPE backend. This populates your agent's knowledge base with current dataset identifiers. Follow up with `get_collection` to pull deep metadata for a specific sensor. This gives your agent the context it needs to build complex queries for your BigQuery pipelines.

Find satellite items

Run `search_items` to locate imagery based on spatial and temporal constraints. Your agent can then feed these results directly into Vertex AI workflows for further analysis. Use `list_collection_items` when you need a full list of captures for a specific project. It handles the heavy lifting of iterating through the catalog so your agent stays focused on logic.

Maintain catalog stability

Invoke `get_root_catalog` to verify the STAC entry point. It’s the standard way to ensure your agent starts its search from the correct base URL. Use `get_conformance` to verify the server's STAC compliance level. This prevents your agent from attempting features that the underlying INPE endpoint might not support.

Setup guide

Set up INPE (STAC API - Satélites) MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with INPE (STAC API - Satélites) tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="INPE (STAC API - Satélites)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to INPE (STAC API - Satélites) tools via MCP.",
    tools=mcp_tools,
)

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Common questions about INPE (STAC API - Satélites) MCP in Google ADK

Initialize the `McpToolset` with the server URL and add it to your `LlmAgent`. Your agent will then gain access to the six satellite tools.

Yes. Gemini models have huge context windows, allowing them to parse the full JSON responses from `search_items` without truncating data.

They work as standard MCP tools. You can orchestrate these calls within your existing Google Cloud functions or Vertex AI pipelines.

Yes, use the tool_names filter in the `McpToolset` configuration. This lets you hide tools you don't need for a specific agent role.

The server uses ephemeral transport. Your satellite search criteria are encrypted in transit and never stored on the Vinkius infrastructure.

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