INMET (Apitempo - Meteorologia) MCP Server for LangChainGive LangChain 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

GDPR Free for Subscribers

LangChain is the leading Python framework for composable LLM applications. Connect INMET (Apitempo - Meteorologia) through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

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The INMET (Apitempo - Meteorologia) MCP Server for LangChain 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

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "inmet-apitempo-meteorologia": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using INMET (Apitempo - Meteorologia), show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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.

LangChain's ecosystem of 500+ components combines seamlessly with INMET (Apitempo - Meteorologia) through native MCP adapters. Connect 8 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain

When LangChain 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 LangChain via MCP

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

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 8 tools from INMET (Apitempo - Meteorologia) via MCP

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

LangChain provides unique advantages when paired with INMET (Apitempo - Meteorologia) through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine INMET (Apitempo - Meteorologia) MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across INMET (Apitempo - Meteorologia) queries for multi-turn workflows

INMET (Apitempo - Meteorologia) + LangChain Use Cases

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

RAG with live data: combine INMET (Apitempo - Meteorologia) tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query INMET (Apitempo - Meteorologia), synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain INMET (Apitempo - Meteorologia) tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every INMET (Apitempo - Meteorologia) tool call, measure latency, and optimize your agent's performance

Example Prompts for INMET (Apitempo - Meteorologia) in LangChain

Ready-to-use prompts you can give your LangChain 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 LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

INMET (Apitempo - Meteorologia) + LangChain FAQ

Common questions about integrating INMET (Apitempo - Meteorologia) MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.

Can I trace MCP tool calls in LangSmith?

Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.

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