AI agentsWeather
SkyCast-AI
A weather agent where every number in the answer comes from a tool, not the AI's memory
5tools the agent can call, each number from one of them
See the live server (opens in a new tab)See the code on GitHub (opens in a new tab)
Proof you can check:Live demoCode on GitHub
AI agents

Every number comes from a tool, not a guess
Should I bring a jacket to Austin this weekend?
get_forecast()get_outdoor_recommendation(Sat)get_outdoor_recommendation(Sun)
No jacket needed. Austin is forecast to reach 97°F Saturday and 102°F Sunday, both far above the 60°F threshold. Take sunscreen instead, the UV index peaks at 8.4.
Lubo Bali · lubobali.com
The problem
AI chat answers about the real world often sound right and invent the numbers. For anything you act on, every figure needs a source.
What I built
An MCP server with 5 weather tools (current conditions, forecast, advice, severe alerts, compare cities) and a Databricks agent that picks the right tool, calls it and answers from what came back.
Tech & why
Thin tools, adapters that hold every web call, and the judgement (thresholds like 60°F for a jacket) in plain code, published in the tool's own description.
- Python
- MCP
- Databricks
- Agent Bricks
The result
Answers like "No jacket needed: 97°F Saturday and 102°F Sunday", where every number came from a tool call, plus a public live endpoint.
How this agent is built
Every AI agent has the same five parts. Here is what each one is in SkyCast-AI, so you can judge any agent the same way.
- ModelA Databricks Agent Bricks agent.
- HarnessThe agent chooses one of 5 MCP tools, calls it and answers only from the result.
- GuardrailsThresholds live in code and in each tool's description; the public server needs a bearer token; no raw web calls inside a tool.
- KnowledgeLive forecasts from Open-Meteo and severe-weather alerts from the National Weather Service.
- ToolsCurrent weather, forecast, outdoor advice, severe alerts, compare cities.
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