Open-Meteo MCP Server for OpenAI Agents SDK 5 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Open-Meteo through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MCPServerStreamableHttp(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as mcp_server:
agent = Agent(
name="Open-Meteo Assistant",
instructions=(
"You help users interact with Open-Meteo. "
"You have access to 5 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Open-Meteo"
)
print(result.final_output)
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.
The OpenAI Agents SDK auto-discovers all 5 tools from Open-Meteo through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Open-Meteo, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
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 OpenAI Agents SDK 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 OpenAI Agents SDK via MCP
Follow these steps to integrate the Open-Meteo MCP Server with OpenAI Agents SDK.
Install the SDK
Run pip install openai-agents in your Python environment
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Run the script
Save the code above and run it: python agent.py
Explore tools
The agent will automatically discover 5 tools from Open-Meteo
Why Use OpenAI Agents SDK with the Open-Meteo MCP Server
OpenAI Agents SDK provides unique advantages when paired with Open-Meteo through the Model Context Protocol.
Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety
Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure
Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate
First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output
Open-Meteo + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Open-Meteo MCP Server delivers measurable value.
Automated workflows: build agents that query Open-Meteo, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries Open-Meteo, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Open-Meteo tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Open-Meteo to resolve tickets, look up records, and update statuses without human intervention
Open-Meteo MCP Tools for OpenAI Agents SDK (5)
These 5 tools become available when you connect Open-Meteo to OpenAI Agents SDK 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 OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK 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 OpenAI Agents SDK
Common issues when connecting Open-Meteo to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Open-Meteo + OpenAI Agents SDK FAQ
Common questions about integrating Open-Meteo MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
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 OpenAI Agents SDK
Get your token, paste the configuration, and start using 5 tools in under 2 minutes. No API key management needed.