Gachi Data API — Japan Station & Accessibility Data by gachi-tokusuru.com
MCP server · indexed, not reviewed
Hostedvendor's own
Not reviewed
No score, grade or rank. This listing is facts from the official MCP registry and our own checks, and it stays out of the rankings until the panel reviews it.
Deep, obscure Japanese station, accessibility & hazard data for AI agents. English-first.
Facts
- MCP registry
com.gachi-tokusuru/japan-data-api· 1.0.1- Endpoint
https://api.gachi-tokusuru.com/mcp- Website
- api.gachi-tokusuru.com
- GitHub stars
- 1
- Registry entry
- updated 5 Jul 2026
From the official MCP registry, the package registries and our own checks. JSON · Markdown
Why it's listed
- It's published in the registry under gachi-tokusuru.com, a namespace the registry only gives to whoever proves they control that domain.
Being indexed says nothing about quality, and nobody can pay for it. Is this yours? Ask for a review.
Tools it lists 10 · about 4,770 tokens of context · checked 29 minutes ago
| Tool | What it does | Hint |
|---|---|---|
ping | Connection test / health check — call this first to confirm the server is reachable. Returns server identity, deploy version, tool count, station coverage, and the update times of the realtime layers (JMA alerts, train… | read-only |
get_municipality_context | Official Japanese government data for any municipality, one call — housing vacancy (2003–2023), nearest-station ridership trend, hazard categories, land prices, livability counts. No scores, no judgment — official… | read-only |
get_station_context | Same official municipality data as get_municipality_context, resolved from a station: pass a station name (Shinjuku / 新宿 / Musashi-Kosugi) or a Japan Station Master station_id (e.g. st_00001), and it returns the context… | read-only |
get_toilet_by_station | Look up wheelchair-accessible / multipurpose toilets inside a train station, including floor, gender, equipment (wheelchair, ostomate, diaper table) and the nearest exit. Covers 526 Tokyo stations (Tokyo Bureau of… | read-only |
get_public_toilet_by_city | List public toilets in a Japanese municipality, with wheelchair / baby-seat / ostomate flags, address and coordinates. Covers 612 municipalities nationwide (large cities capped at the top 50 results). Municipality names… | read-only |
get_station_hazard | Official disaster-risk categories at a Japanese train station, relayed live from the MLIT 不動産情報ライブラリ (Real Estate Information Library): flood inundation-depth rank, landform / liquefaction classification, and… | read-only |
station_search | Discover Japanese train stations by describing what you want around them, in English or Japanese — "朝ラーメンが食べられて車椅子トイレがある駅", "terminal station with late-night ramen", "水害リスクが低くてラーメンが多い駅". Semantic search over 9,035… | read-only |
get_active_alerts | Live river flood forecasts and landslide alerts for Japan (JMA official). NOT general weather warnings (storm/heavy rain/snow) and NOT earthquakes. Covers JMA 指定河川洪水予報 (river flood forecast, levels 2–5) and 土砂災害警戒情報… | read-only |
get_station_alerts | Live JMA river flood forecasts and landslide alerts affecting a station's prefecture — NOT general weather warnings. Ask by station name in Japanese (新宿) or romaji (Shinjuku). Prefecture-level match (station master is… | read-only |
get_train_status | Live train service status for Tokyo-area lines — delays, suspensions, resumptions. Ask 'is the Yamanote Line running?' by line or station name, English or Japanese. Status enum: normal / delayed / suspended / resumed.… | read-only |
What https://api.gachi-tokusuru.com/mcp answered to tools/list, asked without credentials. answered without the initialize handshake. The token figure is the size of the list as sent, divided by four; a model sees about that much before it calls anything. Full definitions, input schemas included, are in the listing's JSON under mcpTools.
How its tools read to an agent 0 errors · 0 warnings · 0 notes
Nothing to flag: every tool reads cleanly to an agent.
The checks from /check and anchor check, run each day on the list above: about 4,770 tokens of definitions. Not part of the score yet. Check your own server.