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Gachi Data API — Japan Station & Accessibility Data

REMOTE · API.GACHI-TOKUSURU.COM · SCANNED AUG 3

Deep, obscure Japanese station, accessibility & hazard data for AI agents. English-first.

+1 this week 66 Trust /100
Trust breakdown (6 categories)

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. How we score →

Endpoint Security66
Transport & Reachability100
Schema Quality & AI Usability64
  • AI-judged instruction clarity (excellent).Pass
  • Context-footprint check failed: tool/resource definitions use about 1984 tokens (~198/item across 10 items; 10 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management27
  • Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
  • 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
  • 100% of tool parameters carry a description.Pass
  • Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass
Capabilities60
  • Spec-recency check failed: implements MCP spec 2025-06-18; the latest is 2026-07-28. See how to fix → Fail
Install

Add this component to your MCP client. Where a client-specific snippet is available, pick your client below and copy it straight into your config; otherwise use the connection detail shown.

remote · api.gachi-tokusuru.com

# add to Claude Code
claude mcp add --transport http com-gachi-tokusuru-japan-data-api https://api.gachi-tokusuru.com/mcp
# ~/.codex/config.toml
[mcp_servers.com-gachi-tokusuru-japan-data-api]
url = "https://api.gachi-tokusuru.com/mcp"
// opencode.json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "com-gachi-tokusuru-japan-data-api": {
      "type": "remote",
      "url": "https://api.gachi-tokusuru.com/mcp",
      "enabled": true
    }
  }
}
# add to OpenClaw
openclaw mcp add com-gachi-tokusuru-japan-data-api --url https://api.gachi-tokusuru.com/mcp --transport streamable-http
# ~/.hermes/config.yaml
mcp_servers:
  com-gachi-tokusuru-japan-data-api:
    url: "https://api.gachi-tokusuru.com/mcp"
// mcp.json
{
  "mcpServers": {
    "com-gachi-tokusuru-japan-data-api": {
      "type": "http",
      "url": "https://api.gachi-tokusuru.com/mcp"
    }
  }
}

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

Changelog

Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.

  • 2 Aug 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 20 to 23. That category is still filling its 30-day observation window: 6 days of observed history at the previous scan, 7 at this one. The score rises as the window fills, whether or not the server changes.

  • 31 Jul 26 0
    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
  • 30 Jul 26 −1
    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
  • 29 Jul 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 7 to 10. That category is still filling its 30-day observation window: 2 days of observed history at the previous scan, 3 at this one. The score rises as the window fills, whether or not the server changes.

  • 27 Jul 26 +1
    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
  • 26 Jul 26 64

    First indexed and scored.

Diagnostics

Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.

Captured 3 Aug 2026 · Probed https://api.gachi-tokusuru.com/mcp

TLS valid

Negotiated TLS 1.3 with TLS_AES_128_GCM_SHA256 .

Subject Issuer Valid from Valid until Key Signature Serial
CN=gachi-tokusuru.com CN=WE1,O=Google Trust Services,C=US 4 Jul 2026 2 Oct 2026 ECDSA 256 ECDSA-SHA256 eab063da07ba61890ed1a9789520e834
SANs: gachi-tokusuru.com, api.gachi-tokusuru.com, *.api.gachi-tokusuru.com
CN=WE1,O=Google Trust Services,C=US (CA) CN=GTS Root R4,O=Google Trust Services LLC,C=US 13 Dec 2023 20 Feb 2029 ECDSA 256 ECDSA-SHA384 7ff31977972c224a76155d13b6d685e3
CN=GTS Root R4,O=Google Trust Services LLC,C=US (CA) CN=GlobalSign Root CA,OU=Root CA,O=GlobalSign nv-sa,C=BE 15 Nov 2023 28 Jan 2028 ECDSA 384 SHA256-RSA 7fe530bf331343bedd821610493d8a1b
DNSSEC secure

Validation of api.gachi-tokusuru.com. Secure

Zone DS Keys Algorithms Outcome
. trust_anchor 20326, 38696 8, 8 Verified
com. present 19718 13 Verified
gachi-tokusuru.com. present 2371 13 Verified
api.gachi-tokusuru.com. Verified address RRset verified with the apex keys
Authentication No authorisation required

The endpoint answered without asking for a token. Anyone who knows the URL can reach it.

Result No authorisation required
HTTP status 200
Transports 2 probes
Transport URL Outcome Status Location
streamable-http https://api.gachi-tokusuru.com/mcp Verified 200
http (plaintext) http://api.gachi-tokusuru.com/mcp Inconclusive 405
MCP tools — 10 exposed · ~1,984 tokens

The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability.

Tool Tokens
get_active_alerts ~169

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 (landslide warning), each with level, affected area, official summary and issue time. Optional `area` filters by 2-digit prefecture code (e.g. 13 = Tokyo) or a JMA forecast-area code. Relay of official facts — not a warning issued by this service, not a life-safety system.

NameTypeReqDescription
areastringOptional prefecture code (01–47, e.g. 13 = Tokyo) or JMA forecast-area code.
NameTypeReqDescription
alertsarrayActive JMA river-flood / landslide alerts with level, area, summary, issue time.
attributionData source(s), license and provenance — an object, or an array of sources.
countNumber of active alerts.
coverageWhat this feed covers — string or array of categories.
disclaimerRelay disclaimer (not a warning issued by this service).
fetched_atWhen the snapshot was fetched.
sourceSource label.
staleTrue if the snapshot is stale.

No examples provided.

get_municipality_context ~150

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 values only. Accepts a 5-digit municipality code (13104) or an exact name (Shinjuku-ku / 新宿区).

NameTypeReqDescription
fieldsstringOptional comma-separated subset: vacancy,ridership,population,hazard,land_price,livability.
name_or_codestringyes5-digit 全国地方公共団体コード (e.g. 13104) or exact municipality name (Shinjuku-ku / 新宿区).
NameTypeReqDescription
attributionData source(s), license and provenance — an object, or an array of sources.
hazardHazard categories.
hazard_disclaimerHazard usage disclaimer.
land_pricePublished land prices near the centroid.
livabilityLivability counts.
municipalityResolved municipality + code.
populationPopulation / future estimate.
ridershipNearest-station ridership trend.
vacancyHousing-vacancy counts (2003–2023).

No examples provided.

get_public_toilet_by_city ~113

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 accept Japanese (e.g. 那覇市, 渋谷区); prefixing the prefecture improves accuracy.

NameTypeReqDescription
citystringyesMunicipality name in Japanese (e.g. 那覇市, 渋谷区, 上天草市). Prefix the prefecture for accuracy.
NameTypeReqDescription
attributionData source(s), license and provenance — an object, or an array of sources.
cityResolved municipality.
countToilets returned.
errorSet when nothing was found.
noteHuman-readable note.
toiletsarrayPublic toilets with wheelchair / baby-seat / ostomate flags, address and coordinates.

No examples provided.

get_station_alerts ~91

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 Greater Tokyo). Relay of official JMA facts.

NameTypeReqDescription
station_namestringyesStation name in Japanese (新宿) or romaji (Shinjuku).
NameTypeReqDescription
alertsarrayJMA alerts affecting the prefecture.
attributionData source(s), license and provenance — an object, or an array of sources.
countNumber of alerts.
disclaimerRelay disclaimer.
fetched_atWhen the snapshot was fetched.
staleTrue if stale.
stationResolved station.

No examples provided.

get_station_context ~161

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 for that station's municipality. Official values only — no scores.

NameTypeReqDescription
fieldsstringOptional comma-separated subset: vacancy,ridership,population,hazard,land_price,livability.
station_idstringJapan Station Master station_id (e.g. st_00001). Alternative to station_name.
station_namestringStation name in English/romaji (Shinjuku) or Japanese (新宿). Provide this or station_id.
NameTypeReqDescription
attributionData source(s), license and provenance — an object, or an array of sources.
hazardHazard categories.
land_priceLand prices near the centroid.
livabilityLivability counts.
municipalityMunicipality + code.
populationPopulation / future estimate.
ridershipRidership trend.
stationResolved station.
vacancyHousing-vacancy counts.

No examples provided.

get_station_hazard ~181

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 storm-surge inundation-area presence (landslide & tsunami are license-restricted and return available:false with a link to the official maps). Returns the official values/categories as-is — no composite score, no judgment. Accepts a station name in Japanese (新宿, 武蔵小杉) or romaji (Shinjuku, Musashi-Kosugi). For research/analytics; NOT a substitute for official government hazard maps or evacuation decisions.

NameTypeReqDescription
station_namestringyesStation name in Japanese (新宿, 武蔵小杉) or romaji (Shinjuku, Musashi-Kosugi).
NameTypeReqDescription
attributionData source(s), license and provenance — an object, or an array of sources.
disclaimerUsage disclaimer (not a substitute for official maps).
hazardOfficial categories: flood inundation depth, landform/liquefaction, storm-surge.
stationResolved station + coordinates.

No examples provided.

get_toilet_by_station ~175

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 Social Welfare data). Major stations outside Tokyo (Yokohama, Kawasaki, Omiya, Chiba, Fujisawa, Shin-Yokohama…) return an in-station layer that groups accessible toilets by ticket gate — inside vs outside — per railway operator. Accepts Japanese (新宿, 横浜) or romaji (Shinjuku, Yokohama) for major stations.

NameTypeReqDescription
stationstringyesStation name in Japanese (新宿, 渋谷) or romaji for major stations (Shinjuku, Shibuya, Kita-Senju).
NameTypeReqDescription
attributionData source(s), license and provenance — an object, or an array of sources.
countToilets returned.
errorSet when nothing was found.
layerData layer (e.g. in_station_gate).
noteHuman-readable note.
sourceData source label.
stationResolved station (English).
station_jaStation name in Japanese.
station_name_sourceHow the name was resolved.
toiletsarrayAccessible toilets with floor, gender, equipment and nearest exit.

No examples provided.

get_train_status ~117

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. Cause text relayed from ODPT (English summary for known patterns, else original text + null). Data via ODPT (CC BY 4.0).

NameTypeReqDescription
querystringyesLine or station name (English or Japanese), e.g. "Yamanote" or "新宿".
NameTypeReqDescription
attributionData source(s), license and provenance — an object, or an array of sources.
countNumber of lines.
fetched_atWhen the snapshot was fetched.
linesarrayPer-line status: normal / delayed / suspended / resumed, with cause.
queryEcho of the query.
staleTrue if stale.

No examples provided.

ping ~71

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 status) so you can confirm freshness, not just liveness. No auth, no arguments, lightweight.

Input schema present but exposes no named parameters.

NameTypeReqDescription
rate_limit_noauthNo-auth rate limit.
realtime_layersobjectUpdate times of the realtime KV snapshots (a field is omitted if that layer is unavailable).
serverServer name.
stations_coveredStations with accessible-toilet data.
statusAlways "ok" when the server is reachable.
toolsNumber of tools exposed by this server.
versionDeploy version.

No examples provided.

station_search ~756

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 station profiles (lines/terminal size, ramen density & styles, in-station accessible-toilet equipment, official hazard categories, ridership) with hybrid metadata filters — the filters guarantee the constraint, the embedding ranks by fit. Filter intent in the query text (朝ラー/深夜/おむつ/車椅子/水害リスク低…) is auto-applied (filter_source: inferred); explicit params win. Water-hazard intent (水害/洪水/浸水/高潮…リスク低) expands to flood rank AND storm-surge zone; 液状化/地盤 intent filters on the official liquefaction-tendency category; results carry risk_notes when other official hazard categories are high. Inferred facility filters with partial data coverage (おむつ/車椅子 — Tokyo-only data) BOOST confirmed stations instead of excluding unknowns (see soft_filters); explicit params remain strict. Taste/quality words (うまい, "good food", delicious…) are not evaluated (no review data); ramen ranking reflects shop density and style variety only. name_contains gives exact substring matching on station names (日本語/romaji) when the name itself is the requirement. Coverage notes: toilet stats = Tokyo stations only; ridership = Greater Tokyo operators only; hazard = official MLIT categories relayed as-is, NOT a safety judgment. Role split: station_search finds candidate stations — then get_toilet_by_station / search_ramen / get_station_hazard / get_station_context for detail on one station.

NameTypeReqDescription
accessible_toilet_minnumberRequire at least this many in-station accessible toilets (Tokyo stations only; auto-inferred from 車椅子/wheelchair…).
diaperbooleanRequire a diaper changing table in station toilets (auto-inferred from おむつ/子連れ…).
flood_rank_maxnumberMax official flood inundation-depth rank 0–6 (0 = no assumed inundation; auto-inferred from 水害リスク低/flood-safe…).
late_ramenbooleanRequire late-night ramen nearby (auto-inferred from 深夜/late night…).
limitnumberMax results (default 10; max 20, or 300 when name_contains is given — set limit >= name_matches_total for exhaustive name-match coverage).
morning_ramenbooleanRequire morning-ramen availability nearby (auto-inferred from 朝ラー/morning…).
name_containsstringSubstring filter on the station name (matches both 日本語 name_ja and romaji name, e.g. "谷" or "sakura"). ANDs with other filters; q still ranks the matches. Use for "stations whose name contains X" req…
prefstringOptional prefecture filter, Japanese (東京都, 千葉 OK) or romaji (tokyo/osaka). Auto-inferred from the query text when omitted.
qstringyesNatural-language description of the station/area you want (ja/en). Concrete attribute words (朝ラー, wheelchair toilet, terminal, 水害リスク低) match best.
ramen_minnumberRequire at least this many ramen shops nearby (e.g. 30).
NameTypeReqDescription
applied_filtersHard metadata filters actually applied (explicit + inferred; includes name_contains when given).
attributionData source(s), license and provenance — an object, or an array of sources.
countResults returned.
disclaimerHazard usage disclaimer.
filter_sourceexplicit / inferred / none — how the filters were chosen.
name_matches_totalTotal stations whose name matched name_contains (before ranking/limit). Present only in name_contains mode.
notePresent when the query contains taste/quality words: they are not evaluated (no review data).
notesCoverage caveats (toilet stats Tokyo-only, ridership Greater-Tokyo-only).
queryEcho of the query.
soft_filtersarrayInferred facility filters applied as a score BOOST (confirmed stations get +BOOST on similarity = final_score; unknown/missing never excluded), with coverage note. Present only when active.
stationsarrayMatching stations, best first: name, pref, similarity, ramen stats, toilet stats, official hazard categories (plus risk_notes when an official hazard category not covered by the filter is high), line…
stats_as_ofFreshness of the underlying ramen stats (YYYY-MM-DD).

No examples provided.