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Glama

Weather MCP Server

by JessiP23

Setup & Run (concise)

Clone & install

git clone https://github.com/JessiP23/mcp.git cd mcp/weather # Python venv python -m venv .venv source .venv/bin/activate pip install -U pip

Install uv (runtime)

macOS / Linux

curl -LsSf https://astral.sh/uv/install.sh | sh # restart terminal after install

Windows (PowerShell)

iwr -useb https://astral.sh/uv/install.ps1 | iex # restart shell after install

Create project with uv (optional)

uv init weather cd weather uv venv source .venv/bin/activate uv add "mcp[cli]" httpx touch weather.py

Run

  1. Install Inspector (if needed):

npx @modelcontextprotocol/inspector@latest --version
  1. Run the MCP server via Inspector:

npx @modelcontextprotocol/inspector uv --directory /Users/jessipavia/mcp/weather run python main.py
  1. (Optional) Run manual search locally:

python main.py --manual

Test files (concise)

  • Copy a local file into samples/:

cp /path/to/local/file.txt samples/
  • Download an online file into samples/:

curl -L "https://example.com/file.txt" -o samples/file.txt
Deploy Server
A
security – no known vulnerabilities
F
license - not found
A
quality - confirmed to work

local-only server

The server can only run on the client's local machine because it depends on local resources.

Enables weather data retrieval and analysis through an MCP server interface with support for local file operations.

  1. Clone & install
    1. Install uv (runtime)
      1. Create project with uv (optional)
        1. Run
          1. Test files (concise)

            MCP directory API

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            curl -X GET 'https://glama.ai/api/mcp/v1/servers/JessiP23/mcp'

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