Nephyr Weather

io.github.clm-studiosPublished by GitHub account clm-studiosv0.1.1Updated Oct 24, 2026

GFS ensemble weather signals for prediction market edge detection across 12 cities

VerifiedSTDIODesktop onlyLocation & LifestyleFinance

Overview

AI-generated overview

A local MCP server that supplies GFS ensemble weather signals for 12 cities, aimed at spotting edges in prediction markets.

What you can do
Provides GFS ensemble weather signals for 12 cities, framed as inputs for prediction market edge detection. No tool list is published, so the exact operations an assistant can call are not documented. Runs as a local process on the user's machine over stdio.
When to use it
Consider it when you want an assistant to weigh ensemble weather forecasts for the covered cities against weather-related prediction market positions. It is not a general-purpose weather service for everyday forecasts.
Requirements
A local Python runtime able to run the nephyr-weather package with uvx. No authentication, environment variables or headers are declared. Desktop only; no web executable.
Before you install
The tool list and documentation are not published, so capabilities are unverified beyond the one-line description. Signals are framed for market edge detection and should not be treated as financial advice; any trading decisions remain the user's.

Installation

In SourceWeft

  1. Open Nephyr Weather in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

This repository has no README.

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v0.1.1LatestSep 16, 2026

Score

25% of the applicable checks met

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  • Reached in the last 30 days25 pts

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  • DescriptionRequired15 pts
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  • Documentation15 pts

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  • License10 pts

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