Realestate Library MCP Server
@miyatsuko10004/realestate-library-mcp
npm
v2.0.0
Source verified
Published by miyatsuko10004 — publish provenance cryptographically ties this package to that repository. That is proof of origin, not an official vendor package.
MCP server for accessing real estate information from MLIT Japan's Real Estate Information Library
The grade answers one question — how safe is this server for you to adopt — so it is computed in two auditable stages. Nothing below is an opinion or an LLM's guess; every line is a real term the deterministic engine applied, and the same input always yields the same number.
1. Threat score — 100 − 0 = 100. What the published surface and source actually contain:
The deterministic scan raised no scored threat in the surface it inspected — the threat score stayed at 100. Capability observations and advisory notes are recorded but never lower it.
2. Client adoption risk — 100 − 0 = 100. Three small, subtract-only factors that reflect your risk in adopting it — a clean scan proves less on a powerful, unverified or barely-inspectable package, so the grade says so plainly:
✓ No adoption-risk deductions — minimal blast radius, verified enough, and fully inspected.
Capability observations and info notes are shown under Findings but never scored.
Open any row's finding below for the file, line and evidence behind a deduction.
Findings 0
Tools 35
Each tool and what it can reach — statically extracted from the published source.
getAppraisalno sensitive capabilitygetChildcareFacilityno sensitive capabilitygetDensityPopulationAreano sensitive capabilitygetDisasterHazardAreano sensitive capabilitygetDisasterHistoryno sensitive capabilitygetDistrictPlanno sensitive capabilitygetElementarySchoolDistrictno sensitive capabilitygetEmergencyEvacuationSiteno sensitive capabilitygetFirePreventionZoneno sensitive capabilitygetFloodInundationAreano sensitive capability
Show 25 more tools ↓
getHighDensityUtilizationAreano sensitive capabilitygetJuniorHighSchoolDistrictno sensitive capabilitygetLandPricePointsno sensitive capabilitygetLandslidePreventionAreano sensitive capabilitygetLandUseZoneno sensitive capabilitygetLargeFilledLandno sensitive capabilitygetLibraryno sensitive capabilitygetLiquefactionTendencyno sensitive capabilitygetLocationOptimizationPlanno sensitive capabilitygetMedicalFacilityno sensitive capabilitygetMunicipalitiesno sensitive capabilitygetMunicipalOfficeno sensitive capabilitygetNaturalParkno sensitive capabilitygetPopulationMeshno sensitive capabilitygetRealEstatePriceno sensitive capabilitygetRealEstatePricePointsno sensitive capabilitygetSchoolno sensitive capabilitygetSedimentDisasterHazardAreano sensitive capabilitygetStationPassengersno sensitive capabilitygetSteepSlopeHazardAreano sensitive capabilitygetStormSurgeInundationAreano sensitive capabilitygetTsunamiInundationAreano sensitive capabilitygetUrbanPlanningDistrictno sensitive capabilitygetUrbanPlanningRoadno sensitive capabilitygetWelfareFacilityno sensitive capability
What this scan could not see
- Tools were statically extracted from the published source (35 recovered), not enumerated from a running server. Tool-poisoning, Unicode-smuggling, capability and toxic-flow analysis ran on this inferred surface, but a mis-parsed registration could be missed or mis-attributed, so tool-derived findings are capped below “confirmed”. To grade the real runtime surface, scan the running server: --command "npx -y <package>".
Versions 1
Scan history per published version. The engine is deterministic — the same version always yields the same score, so a changed score means the package itself changed.
| Version | Score | Findings | Engine | Scanned |
|---|---|---|---|---|
v2.0.0 latest |
A 100/100 | 0 | 1.13.0 | 2026-09-07 |
Embed this score
Show this server's live Trust Score in your README, docs or website. The badge is served straight from the registry and updates automatically after every rescan — no API key needed. It links back to this page, so anyone who sees the grade can also read the findings behind it instead of taking a number on faith.
Verify this score yourself
The score above is reproducible: the same package version always yields the same result. Run it locally or over the free API — no account, no LLM, fully deterministic.
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