Open-Meteo MCP Server for LangChain 5 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Open-Meteo through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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({
"open-meteo": {
"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 Open-Meteo, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* 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 MCP Server
Connect to Open-Meteo and access global weather forecasts through natural conversation — no API key needed.
LangChain's ecosystem of 500+ components combines seamlessly with Open-Meteo through native MCP adapters. Connect 5 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
- Current Weather — Get real-time temperature, humidity, wind, precipitation and conditions
- 7-Day Forecast — Hourly and daily forecasts up to 16 days ahead with 50+ weather variables
- Historical Weather — Access archived weather data going back to 1940 for any location
- Air Quality — Get PM2.5, PM10, NO2, O3, SO2, CO and UV index forecasts
- Geocoding — Find coordinates for any city or place name
- Elevation — Get elevation data for any coordinates
The Open-Meteo MCP Server exposes 5 tools through the Vinkius. Connect it to LangChain 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 to LangChain via MCP
Follow these steps to integrate the Open-Meteo MCP Server with LangChain.
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 5 tools from Open-Meteo via MCP
Why Use LangChain with the Open-Meteo MCP Server
LangChain provides unique advantages when paired with Open-Meteo through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Open-Meteo 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 Open-Meteo queries for multi-turn workflows
Open-Meteo + LangChain Use Cases
Practical scenarios where LangChain combined with the Open-Meteo MCP Server delivers measurable value.
RAG with live data: combine Open-Meteo tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Open-Meteo, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Open-Meteo tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Open-Meteo tool call, measure latency, and optimize your agent's performance
Open-Meteo MCP Tools for LangChain (5)
These 5 tools become available when you connect Open-Meteo to LangChain via MCP:
get_air_quality
5, PM10, nitrogen dioxide, ozone, sulphur dioxide, carbon monoxide, dust, pollen and UV index. Requires latitude and longitude. Returns hourly data for up to 7 days. Common variables: pm2_5, pm10, nitrogen_dioxide, ozone, sulphur_dioxide, carbon_monoxide, dust, uv_index, alder_pollen, grass_pollen. Get air quality forecast for a location
get_elevation
Useful for hiking, aviation and geographic research. Get elevation for coordinates
get_forecast
Requires latitude and longitude. Supports hourly, daily and current weather variables. Common variables: temperature_2m, relative_humidity_2m, precipitation, rain, snowfall, wind_speed_10m, wind_direction_10m, wind_gusts_10m, weather_code, cloud_cover, pressure_msl, uv_index, visibility, apparent_temperature, dew_point_2m, sunshine_duration. Set past_days to include historical data (0-92 days). Set forecast_days for forecast length (0-16 days, default 7). Timezone defaults to GMT; use "auto" for local timezone. Get weather forecast for a location
get_geocoding
Useful for finding coordinates to use with weather tools. Returns up to 10 results by default. Find coordinates for a place name
get_historical_weather
Requires latitude, longitude, start date and end date (YYYY-MM-DD format). Supports the same hourly variables as the forecast API. Historical data goes back to 1940 for most locations. Use get_geocoding to find coordinates for a city name. Get historical weather data for a location
Example Prompts for Open-Meteo in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Open-Meteo immediately.
"What's the weather forecast for São Paulo this week?"
"What was the temperature in Tokyo on July 15, 2024?"
"What's the air quality in Beijing right now?"
Troubleshooting Open-Meteo MCP Server with LangChain
Common issues when connecting Open-Meteo to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersOpen-Meteo + LangChain FAQ
Common questions about integrating Open-Meteo MCP Server with LangChain.
How does LangChain connect to MCP servers?
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?
Can I trace MCP tool calls in LangSmith?
Connect Open-Meteo with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Open-Meteo to LangChain
Get your token, paste the configuration, and start using 5 tools in under 2 minutes. No API key management needed.