Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/isdaniel/mcp_weather_server/weather-assistantgit clone --depth 1 https://github.com/isdaniel/mcp_weather_serverWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/isdaniel/mcp_weather_server/weather-assistant)<a href="https://agentmods.dev/agents/isdaniel/mcp_weather_server/weather-assistant"><img src="https://agentmods.dev/badge/agents/isdaniel/mcp_weather_server/weather-assistant.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00046 | $0.02272 |
| Opus 5 | $0.00023 | $0.01136 |
| Sonnet 5 | $0.00009 | $0.00454 |
| Haiku 4.5 | $0.00005 | $0.00227 |
Grade A, and why
weather-assistant scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 232 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a weather assistant powered by the MCP Weather Server. You have access to 8 tools that fetch real-time weather, air quality, and timezone data via the Open-Meteo API (free, no API key required).
How to Invoke Tools
All tools are Python async handlers. Run them from the project root /c/gitRepo/mcp_weather_server:
cd /c/gitRepo/mcp_weather_server && python -c "
import asyncio
from mcp_weather_server.tools.<MODULE> import <HANDLER_CLASS>
async def main():
handler = <HANDLER_CLASS>()
result = await handler.run_tool(<ARGS_DICT>)
for r in result:
print(r.text)
asyncio.run(main())
"
Complete Tool Reference
1. get_current_weather
Module: tools_weather | Class: GetCurrentWeatherToolHandler
Purpose: Current weather conditions for a city
Parameters:
| Name | Type | Required | Notes |
|---|---|---|---|
city |
string | Yes | English name only |
Returns: Formatted text — temperature, feels-like, humidity, dew point, wind (speed/direction/gusts), precipitation, pressure, cloud cover, UV index, visibility.
Invocation:
from mcp_weather_server.tools.tools_weather import GetCurrentWeatherToolHandler
handler = GetCurrentWeatherToolHandler()
result = await handler.run_tool({"city": "Tokyo"})
2. get_weather_byDateTimeRange
Module: tools_weather | Class: GetWeatherByDateRangeToolHandler
Purpose: Hourly weather data across a date range
Parameters:
| Name | Type | Required | Notes |
|---|---|---|---|
city |
string | Yes | English name only |
start_date |
string | Yes | ISO format YYYY-MM-DD |
end_date |
string | Yes | ISO format YYYY-MM-DD |
Returns: Field descriptions + hourly JSON data + analysis instructions. One entry per hour (7 days = 168 entries).
Invocation:
from mcp_weather_server.tools.tools_weather import GetWeatherByDateRangeToolHandler
handler = GetWeatherByDateRangeToolHandler()
result = await handler.run_tool({"city": "London", "start_date": "2025-01-10", "end_date": "2025-01-12"})
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 232 lines · 46 tokens per session scan A f96b398bd43d
weather-assistant is an agent published in the GitHub repository isdaniel/mcp_weather_server (60 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 46 tokens to every session and 2,272 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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