INMET (Apitempo - Meteorologia) MCP Server for Google ADKGive Google ADK instant access to 8 tools to Get All Forecasts, Get Forecast By City, Get Meteorological Data By Date, and more

Name: INMET (Apitempo - Meteorologia)
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

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Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add INMET (Apitempo - Meteorologia) as an MCP tool provider through Vinkius and your ADK agents can call every tool with full schema introspection.

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The INMET (Apitempo - Meteorologia) MCP Server for Google ADK is a standout in the Government Public Data category — giving your AI agent 8 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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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="inmet_apitempo_meteorologia_agent",
    instruction=(
        "You help users interact with INMET (Apitempo - Meteorologia) "
        "using 8 available tools."
    ),
    tools=[mcp_tools],
)

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About INMET (Apitempo - Meteorologia) MCP Server

Connect to the INMET (Instituto Nacional de Meteorologia) API to retrieve comprehensive weather data across Brazil. This server allows AI agents to query a vast network of automatic and manual stations, providing precise atmospheric measurements and forecasts.

Google ADK natively supports INMET (Apitempo - Meteorologia) as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 8 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

Meteorological Stations — List all automatic (T) and manual (M) stations across the Brazilian territory.
Historical & Real-time Data — Fetch daily or hourly measurements (temperature, humidity, pressure) for specific station IDs.
Regional Analysis — Query data for all stations within specific Brazilian regions (N, NE, CO, SE, S) for a given date.
Weather Forecasts — Get detailed forecasts for cities using IBGE codes or retrieve all available forecasts at once.
Satellite Imagery — Access the latest GOES-16 satellite metadata and image URLs for visual weather monitoring.

The INMET (Apitempo - Meteorologia) MCP Server exposes 8 tools through the Vinkius. Connect it to Google ADK in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 8 INMET (Apitempo - Meteorologia) tools available for Google ADK

When Google ADK connects to INMET (Apitempo - Meteorologia) through Vinkius, your AI agent gets direct access to every tool listed below — spanning meteorology, brazil-weather, weather-forecast, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

get

Get all forecasts on INMET (Apitempo - Meteorologia)

Get weather forecasts for all supported cities

get

Get forecast by city on INMET (Apitempo - Meteorologia)

Get weather forecast for a specific city

get

Get meteorological data by date on INMET (Apitempo - Meteorologia)

Get meteorological data by date for a station

get

Get meteorological data by region on INMET (Apitempo - Meteorologia)

Get meteorological data for all stations in a specific region

get

Get satellite images on INMET (Apitempo - Meteorologia)

Get latest GOES-16 satellite images

get

Get station data daily on INMET (Apitempo - Meteorologia)

Get daily meteorological data for a specific station

get

Get station data hourly on INMET (Apitempo - Meteorologia)

Get hourly data for a specific station and time

list

List stations on INMET (Apitempo - Meteorologia)

List meteorological stations by type

Connect INMET (Apitempo - Meteorologia) to Google ADK via MCP

Follow these steps to wire INMET (Apitempo - Meteorologia) into Google ADK. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

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 8 tools from INMET (Apitempo - Meteorologia) via MCP

Why Use Google ADK with the INMET (Apitempo - Meteorologia) MCP Server

Google ADK provides unique advantages when paired with INMET (Apitempo - Meteorologia) 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 INMET (Apitempo - Meteorologia)

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 INMET (Apitempo - Meteorologia) tools with BigQuery, Vertex AI, and Cloud Functions

INMET (Apitempo - Meteorologia) + Google ADK Use Cases

Practical scenarios where Google ADK combined with the INMET (Apitempo - Meteorologia) MCP Server delivers measurable value.

Enterprise data agents: ADK agents query INMET (Apitempo - Meteorologia) and cross-reference results with internal databases for comprehensive analysis

Multi-modal workflows: combine INMET (Apitempo - Meteorologia) tool responses with Gemini's vision and language capabilities in a single agent

Automated compliance checks: schedule ADK agents to query INMET (Apitempo - Meteorologia) regularly and flag policy violations or configuration drift

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including INMET (Apitempo - Meteorologia)

Example Prompts for INMET (Apitempo - Meteorologia) in Google ADK

Ready-to-use prompts you can give your Google ADK agent to start working with INMET (Apitempo - Meteorologia) immediately.

"List all automatic weather stations in Brazil."

"What is the weather forecast for city code 3304557?"

"Show me the latest satellite images from GOES-16."

Troubleshooting INMET (Apitempo - Meteorologia) MCP Server with Google ADK

Common issues when connecting INMET (Apitempo - Meteorologia) to Google ADK through Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

INMET (Apitempo - Meteorologia) + Google ADK FAQ

Common questions about integrating INMET (Apitempo - Meteorologia) 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.