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JessiP23

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

Available Tools

1 tool
search_keywordD
ParametersJSON Schema
NameRequiredDescriptionDefault
file_pathYes
keywordYes

TDQS

D1/5.0
Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Tool has no description.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness1/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Tool has no description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool has no description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Tool has no description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose1/5

Does the description clearly state what the tool does and how it differs from similar tools?

Tool has no description.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Tool has no description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool updatev1.0.0
    • First observedsearch_keyword

TDQS

D1.7/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools, as there are no other tools to compare it against. The tool 'search_keyword' stands alone with a distinct purpose.

Naming Consistency5/5

With only one tool, naming consistency is inherently perfect as there is no variation or pattern to deviate from. The tool name 'search_keyword' follows a clear verb_noun structure, but this cannot be assessed for consistency across multiple tools.

Tool Count2/5

A single tool for a 'Weather MCP Server' is too few for the apparent scope, as weather-related tasks typically involve multiple operations like getting current conditions, forecasts, or alerts. This minimal set is likely incomplete for practical use.

Completeness1/5

The tool set is severely incomplete for a weather domain, with only a generic 'search_keyword' tool that does not cover essential weather operations such as retrieving current weather, forecasts, or location-based data. This will cause significant agent failures in handling weather-related queries.

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