How far back does the historical data go?

All the way to **January 1, 1940** — that's 84 years of continuous, hourly global weather data powered by ERA5 reanalysis from ECMWF.

Open-Meteo Historical Weather MCP Server for Google ADK 3 tools — connect in under 2 minutes

Name: Open-Meteo Historical Weather
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 3 Tools SDK

Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Open-Meteo Historical Weather as an MCP tool provider through 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

Open in ChatGPT Open in Claude Open in Perplexity

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="open_meteo_historical_weather_agent",
    instruction=(
        "You help users interact with Open-Meteo Historical Weather "
        "using 3 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 Open-Meteo Historical Weather MCP Server

Access 84 years of continuous weather records from 1940 to today for any location on Earth.

Google ADK natively supports Open-Meteo Historical Weather as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 3 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

Historical Hourly — Temperature, humidity, precipitation, snowfall, weather codes, and wind for any past date range
Historical Daily — Max/min temperatures, precipitation totals, sunshine duration, and dominant wind patterns
Temperature Trends — Dedicated tool for long-term climate trend analysis with apparent temperature data

The Open-Meteo Historical Weather MCP Server exposes 3 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 Open-Meteo Historical Weather to Google ADK via MCP

Follow these steps to integrate the Open-Meteo Historical Weather 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 3 tools from Open-Meteo Historical Weather via MCP

Why Use Google ADK with the Open-Meteo Historical Weather MCP Server

Google ADK provides unique advantages when paired with Open-Meteo Historical Weather 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 Open-Meteo Historical Weather

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 Open-Meteo Historical Weather tools with BigQuery, Vertex AI, and Cloud Functions

Open-Meteo Historical Weather + Google ADK Use Cases

Practical scenarios where Google ADK combined with the Open-Meteo Historical Weather MCP Server delivers measurable value.

Enterprise data agents: ADK agents query Open-Meteo Historical Weather and cross-reference results with internal databases for comprehensive analysis

Multi-modal workflows: combine Open-Meteo Historical Weather tool responses with Gemini's vision and language capabilities in a single agent

Automated compliance checks: schedule ADK agents to query Open-Meteo Historical Weather regularly and flag policy violations or configuration drift

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Open-Meteo Historical Weather

Open-Meteo Historical Weather MCP Tools for Google ADK (3)

These 3 tools become available when you connect Open-Meteo Historical Weather to Google ADK via MCP:

get_historical_daily

Get historical daily weather aggregates

get_historical_temperature

Includes hourly temperature, apparent temperature, and dewpoint. Get historical temperature trends for climate analysis

get_historical_weather

Provide latitude, longitude, start_date and end_date in YYYY-MM-DD format. Covers 84 years of global data. Get historical weather for any date range (1940–present)

Example Prompts for Open-Meteo Historical Weather in Google ADK

Ready-to-use prompts you can give your Google ADK agent to start working with Open-Meteo Historical Weather immediately.

"What was the weather in London on D-Day, June 6, 1944?"

"Compare average temperatures in São Paulo between 1950 and 2020"

"How much rain fell in Mumbai during the 2005 flood?"

Troubleshooting Open-Meteo Historical Weather MCP Server with Google ADK

Common issues when connecting Open-Meteo Historical Weather to Google ADK through the Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

Open-Meteo Historical Weather + Google ADK FAQ

Common questions about integrating Open-Meteo Historical Weather 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.