mcp-tenki
# mcp-tenki
A MCP server with weather of Japan
<a href="https://glama.ai/mcp/servers/jbl3sfsi9r"><img width="380" height="200" src="https://glama.ai/mcp/servers/jbl3sfsi9r/badge" alt="Tenki MCP server" /></a>
# Setup
```
$ uv sync
```
# Running Server
Run without clone
```json: {{.HOME}}/Library/Application\ Support/Claude/claude_desktop_config.json
{
"mcpServers": {
"tenki": {
"command": "uvx",
"args": ["--from", "git+https://github.com/acxelerator/mcp-tenki.git", "mcp-tenki"]
}
}
}
```
Run with clone
```json: {{.HOME}}/Library/Application\ Support/Claude/claude_desktop_config.json
{
"mcpServers": {
"tenki": {
"command": "uv",
"args": ["--directory", "/PATH/TO/REPOSITORY/mcp-tenki/mcp_tenki", "run", "main.py"]
}
}
}
```
TDQS
Scored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined as getting forecasts for Japanese locations, making it distinct by default.
The single tool follows a clear verb_noun pattern (get_forecast), which is consistent and predictable. Since there are no other tools, there is no inconsistency to evaluate.
One tool is too few for a weather forecasting server, as it lacks essential operations like searching locations, getting current conditions, or handling multiple forecast types. This minimal scope will likely cause agent failures due to incomplete functionality.
The server is severely incomplete for weather forecasting; it only provides forecasts without supporting related operations like current weather, alerts, or location validation. This creates significant gaps that will hinder agent workflows.