How to Use the AerisWeather MCP in OpenAI Agents SDK

Q: How do I configure AerisWeather with OpenAI Agents SDK?

Install the library via pip, then initialize the MCPServerStreamableHttp client with your Vinkius endpoint. Pass this server instance directly into your Agent constructor's server list.

Q: Can I run batch requests using AerisWeather on OpenAI Agents SDK?

Yes. The getbatch tool lets your agent pack up to 31 distinct requests into a single round-trip. This keeps your latency low and prevents rate-limiting issues.

Q: Why should I set cacheToolsList to true for this MCP Server?

Setting cacheToolsList=True prevents the SDK from querying the Vinkius endpoint for tool definitions on every single turn. It speeds up agent startup times and reduces network noise.

Give your OpenAI Agents SDK production pipelines direct, validated access to real-time AerisWeather data.

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Connect AerisWeather MCP to OpenAI Agents SDK

Create your Vinkius account to connect AerisWeather to OpenAI Agents SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup AerisWeather with OpenAI Agents SDK

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Batch weather queries for OpenAI Agents SDK

Stop making your agent run dozens of individual HTTP requests. When you use this MCP Server, your agent grabs forecasts, current conditions, and active storm warnings in a single call. This saves you money on token overhead and keeps your OpenAI runs fast. You just pass a comma-separated list of targets like `/observations` and `/forecasts`. Combined with `get_places` to resolve airport codes or cities, your agent builds a complete regional weather profile before making its next decision.

Safe weather alerts with built-in guardrails

Production systems cannot afford to let an agent act on stale or hallucinated data. By hooking up the `get_alerts` tool, your agent checks active warnings, watches, and advisories directly from AerisWeather. Because you are using the OpenAI Agents SDK, you can set up guardrails to inspect these alerts before triggering automated SMS blasts or logistics rerouting. The agent checks the threat level, passes the data through your validation layer, and keeps your operations safe.

Precision forecasting on a managed MCP Server

Get hyper-local down to the minute. The `get_conditions` tool supports minutely precipitation forecasts with the `filter=minutelyprecip` flag, covering a range from historical 2004 data up to 15 days out. Your agent uses `get_forecasts` and `get_observations` to compare what is happening right now with what is coming down the pipe. It is the easiest way to give your custom OpenAI agents real-world awareness through our managed MCP Server without writing custom API integrations.

Setup guide

Set up AerisWeather MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all AerisWeather tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives AerisWeather tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate AerisWeather tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="AerisWeather Agent",
            instructions="You have access to AerisWeather tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by AerisWeather. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about AerisWeather MCP in OpenAI Agents SDK

Install the library via pip, then initialize the `MCPServerStreamableHttp` client with your Vinkius endpoint. Pass this server instance directly into your Agent constructor's server list.

Yes. The `get_batch` tool lets your agent pack up to 31 distinct requests into a single round-trip. This keeps your latency low and prevents rate-limiting issues.

Setting `cacheToolsList=True` prevents the SDK from querying the Vinkius endpoint for tool definitions on every single turn. It speeds up agent startup times and reduces network noise.

You can set up specialized weather agents that own the AerisWeather tools. When your main routing agent detects a weather-related query, it hands off the conversation to the weather specialist, which calls `get_observations` or `get_forecasts` to get the answer.

Your coordinates, city names, and airport codes pass through Vinkius to the AerisWeather API to resolve the query. We do not store your location lookups or forecast queries, keeping your operational logistics private.

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