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swiss-housing-mcp

by malkreide

swiss-housing-mcp

Teil des Swiss Public Data MCP Portfolio — Open-Source-MCP-Server, die KI-Agenten mit Schweizer öffentlichen Daten verbinden. Privates Projekt, unabhängig von Arbeitgeber oder institutioneller Zugehörigkeit.

Version License: MIT Python MCP

MCP-Server für das Schweizerische Gebäude- und Wohnungsregister (GWR/RegBL) — Gebäude, Wohnungen und die Bau-Pipeline

🇩🇪 Deutsche Version


🎯 Anker-Demo-Abfrage

«Wie viele Wohnungen wurden seit 2020 in der Stadt Zürich neu gebaut, wie viele mit 4+ Zimmern — und wie viele sind derzeit im Bau?»

Verifiziert gegen den Live-Dump vom 2026-07-24: 16'164 neue Wohnungen seit 2020 (27,4% mit 4+ Zimmern — der Proxy für Familienwohnungen) und 7'287 Wohnungen derzeit im Bau. Wohnungen, die heute im Bau sind, sind Haushalte in 1–3 Jahren: der Frühindikator für die Schulraumplanung.

Demo

Demo: Claude using new_construction and construction_pipeline


Related MCP server: swiss-statistics-mcp

Überblick

Das GWR/RegBL ist für Gebäude das, was Zefix für Unternehmen ist: nicht eine Datenquelle unter vielen, sondern das Bundesregister, dessen Identifikatoren (EGID für Gebäude, EWID für Wohnungen) als Join-Keys über Schweizer Verwaltungsdaten dienen. Dieser Server stellt den öffentlichen Auszug des Registers über MCP-Tools bereit — Gebäudeabfragen, Adress-Geocoding, Baustatistiken pro Gemeinde, Analyse von Teilgemeinden per Bounding-Box und die Planungs-/Bau-Pipeline.

address_to_egid ist der Stecker, der andere Datenquellen EGID-fähig macht: Adresse rein, Bundesidentifikator und LV95-Koordinaten raus.

Architekturentscheidung

Dieser Server verwendet Architektur B (Hybrid: Dump-first, API-Fallback).

Begründung (live verifiziert am 2026-07-24):

  • Der öffentliche Kantons-Dump (public.madd.bfs.admin.ch/{canton}.zip) wird täglich (~05:30 CET) aktualisiert und enthält eine fertige data.sqlite mit den Tabellen building (399'830 Zeilen für ZH), entrance, dwelling (894'631 Zeilen für ZH) und code. Kein CSV-Parsing, keine Authentifizierung.

  • api3.geo.admin.ch (find / identify / SearchServer) funktioniert zuverlässig ohne Authentifizierung für Einzelabfragen und Geocoding, skaliert aber nicht für flächendeckende Aggregationen (Ergebnislimits).

  • Ein MADD-REST-Endpunkt, getestet unter /api/buildings/{egid}, lieferte 404; er ist ausgeschlossen, bis Pfad und Auth-Status geklärt sind — kein Blocker, da alle Phase-1-Tools ohne ihn funktionieren.

Konsequenzen:

  • Kantonale Dumps werden mit einer TTL von 24 h auf der Festplatte zwischengespeichert (konfigurierbar über SWISS_HOUSING_DUMP_TTL_HOURS).

  • Aggregationen und räumliche Abfragen laufen als schreibgeschütztes SQL gegen das gecachte SQLite; Einzelabfragen und Geocoding nutzen die Live-API.

  • Jede Antwort enthält source (Quellenangabe) und provenance (daily_dump | live_api | cached).

Live-Testergebnisse (2026-07-24)

Endpoint

HTTP

Status

Note

api3.geo.admin.ch …/find (EGID lookup)

200

✅ funktioniert

voller Attributsatz, keine Authentifizierung

api3.geo.admin.ch …/identify (coordinates)

200

✅ funktioniert

77 Attribute inkl. EGID/EWID

…/SearchServer (address → EGID)

200

✅ funktioniert

featureId = {EGID}_{EDID}; Achsentausch: y=Osten, x=Norden

public.madd.bfs.admin.ch/zh.zip

200

✅ funktioniert

121 MB, tägliche Aktualisierung, enthält data.sqlite

madd.bfs.admin.ch/api/buildings/{egid}

404

❌ ausgeschlossen

Pfad/Auth unklar

Invalid EGID on find

200

⚠️ weicher Fehler

leeres results-Array — kein HTTP-Fehler

Funktionen

  • lookup_building(egid) — einzelnes Gebäude nach Bundesidentifikator (Live-API)

  • address_to_egid(address) — geokodiert jede Schweizer Adresse zu EGID/EDID + LV95

  • lookup_dwellings(egid) — alle Wohnungen eines Gebäudes mit Zimmern, Fläche, Stockwerk

  • new_construction(municipality_bfs, since_year) — jährlicher Neubau inkl. Anteil Familienwohnungen mit 4+ Zimmern

  • construction_pipeline(municipality_bfs) — geplant / bewilligt / im Bau

  • buildings_in_bbox(e_min, n_min, e_max, n_max) — Analyse auf Teilgemeindeebene (z. B. Schulkreise)

  • municipality_housing_stats(municipality_bfs) — Wohnungsbestand und Zimmergrössen-Mix

  • explain_code(attribute, code) — dekodiert GWR-Codes über die offizielle DE/FR/IT-Codetabelle

  • dump_status() — Cache-Frische, Einstiegspunkt für Graceful Degradation

Voraussetzungen

  • Python 3.10+

  • ~130 MB Speicherplatz pro gecachtem Kantons-Dump (ZH)

  • Keine API-Schlüssel — Phase 1 ist authentifizierungsfrei

Installation

uvx swiss-housing-mcp        # once published on PyPI

# or from source
pip install -e .

Verwendung / Schnellstart

Claude Desktop (claude_desktop_config.json):

{
  "mcpServers": {
    "swiss-housing": {
      "command": "uvx",
      "args": ["swiss-housing-mcp"]
    }
  }
}

Cloud (Render/Railway):

SWISS_HOUSING_TRANSPORT=streamable-http PORT=8000 swiss-housing-mcp

Konfiguration

Variable

Default

Zweck

SWISS_HOUSING_TRANSPORT

stdio

stdio | streamable-http | sse

SWISS_HOUSING_CACHE

~/.cache/swiss-housing-mcp

Dump-Cache-Verzeichnis

SWISS_HOUSING_DUMP_TTL_HOURS

24

Dump-Frische-Fenster

MCP-Protokollversion

Dieser Server spricht zwei Protokoll-Ären über denselben Endpunkt. Die erste Anfrage eines Clients auf einer Verbindung entscheidet, welche gilt; eine spätere Behauptung aus der anderen Ära wird abgelehnt.

Era

Revision

Wer erreicht sie

initialize handshake

2024-11-052025-11-25

Was heutige Clients sprechen. Der Server antwortet mit der angefragten Revision oder mit der 2025-11-25-Obergrenze, wenn die Anfrage etwas Neueres verlangt.

Per-request envelope

2026-07-28

Eine Anfrage mit dem 2026-07-28-_meta-Envelope öffnet eine moderne Verbindung.

Beide Revisionen sind in tests/test_protocol_version.py festgelegt und werden gegen das installierte SDK geprüft, sodass ein Dependabot-Update von mcp keine der beiden stillschweigend verschieben kann. Dieser Server baut keine ASGI-App, um ein initialize durchzuschicken, daher prüft das Gate die SDK-Konstanten statt einer gemessenen Antwort — die schwächere Form, benannt statt unausgesprochen.

Beachten Sie, dass LATEST_PROTOCOL_VERSION des SDK ein Alias für die moderne Ära ist, nicht für die Handshake-Ära — wenn man nur dagegen pinnt, würde die Ära, die aktuelle Clients tatsächlich aushandeln, frei driften.

Update-Richtlinie. Wenn das Gate fehlschlägt, bearbeiten Sie die Konstante nicht blind: Lesen Sie das Spec-Changelog zwischen den beiden Revisionen, verifizieren Sie, dass der Server sich weiterhin korrekt verhält, und verschieben Sie dann die Konstante, diesen Abschnitt, README.de.md und CHANGELOG.md gemeinsam.

Testen

PYTHONPATH=src pytest tests/ -m "not live"   # CI-safe
PYTHONPATH=src pytest tests/ -m live         # against real upstream

Projektstruktur

swiss-housing-mcp/
├── src/swiss_housing_mcp/
│   ├── server.py      # FastMCP tools (9)
│   ├── gwr.py         # Dump store + geo.admin.ch client + retry
│   ├── models.py      # Pydantic v2 envelopes (source + provenance)
│   └── __main__.py    # Dual-transport entry point
├── tests/             # respx-mocked + @pytest.mark.live
└── .github/workflows/ # CI + OIDC PyPI publish

Bekannte Einschränkungen

  • Der öffentliche Auszug lässt personenbezogene und einige sensible Attribute des vollständigen GWR aus; offizielle Datenlieferungen an Behörden laufen über den BFS/MADD-Kanal.

  • Koordinaten sind Gebäude-Referenzpunkte (LV95), keine Grundriss-Polygone — Polygon-Joins (z. B. exakte Schulkreisgrenzen) benötigen externe Geometrien; buildings_in_bbox deckt die rechteckige Näherung ab.

  • GBAUJ (Baujahr) fehlt bei einem Teil älterer Gebäude; Periodencodes (GBAUP) existieren als Fallback, sind aber noch nicht freigeschaltet.

  • Die Auflösung Gemeinde→Kanton ist für häufige Fälle vorbefüllt; für andere explizit canton angeben.

  • Wohnungsmarktindizes (IMPI, Baukostenindex, Leerstandsquote) leben bewusst in swiss-statistics-mcp — dieser Server ist die Registerebene, nicht die Statistik-Ebene.

Changelog

Siehe CHANGELOG.md

Mitwirken

Beiträge sind willkommen — siehe CONTRIBUTING.md (Deutsch).

Sicherheit

Nur lesend, keine personenbezogenen Daten, keine Authentifizierung — ein öffentliches Bundesregister, das über eine feste Reihe von Endpunkten abgerufen wird. Siehe SECURITY.md (Deutsch) für die vollständige Haltung und wie Sie eine Schwachstelle melden.

Lizenz

MIT-Lizenz — siehe LICENSE. Daten: GWR/RegBL, Bundesamt für Statistik (BFS), Open Government Data mit Quellenangabe.

Autor

Hayal Oezkan · github.com/malkreide

Danksagungen & verwandte Projekte

Available Tools

5 tools
construction_pipelineB
Read-only

Buildings and dwellings in the planning/construction pipeline of a municipality.

Breaks down by status: projected (GSTAT 1001), approved (1002), under construction (1003). Dwellings under construction today are households in 1-3 years — the early indicator for school-space planning.

ParametersJSON Schema
NameRequiredDescriptionDefault
cantonNo
municipality_bfsYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
noteNo
sourceNo
pipelineYes
provenanceYes
municipalityYes
municipality_bfsYes

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, so the description's additional information about status breakdowns and the interpretation of 'under construction' as an early indicator adds useful behavioral context. However, it does not disclose potential limitations like data availability by municipality or time-range constraints.

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

Conciseness5/5

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

The description is three concise sentences: the first states the core purpose, the second details the status categories, and the third explains the practical implication. Every sentence adds value, and the content is front-loaded with the most critical information.

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

Completeness3/5

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

Given the presence of an output schema and the tool's moderate complexity, the description covers the data meaning and use case. However, it omits parameter semantics and does not specify what the output contains or how to interpret the status codes fully (though codes are listed). The description is adequate but not comprehensive.

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?

The input schema has 0% description coverage for its two parameters (canton, municipality_bfs). The description does not mention these parameters or provide any guidance on their values, formats, or roles. With no schema descriptions and no parameter information in the description, the agent receives no help beyond the schema structure.

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

Purpose5/5

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

The description clearly specifies the tool retrieves buildings and dwellings in the planning/construction pipeline of a municipality, with explicit breakdowns by status codes. This verb-resource combination is distinct from sibling tools like lookup_dwellings (likely existing dwelling data) and new_construction (new building registrations). The context of early indicator for school-space planning further differentiates its use case.

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

Usage Guidelines3/5

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

The description implies usage for getting pipeline data for a municipality and hints at its value for school-space planning, but it does not explicitly state when to prefer this tool over siblings or when not to use it. No exclusions or alternative recommendations are provided.

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

dump_statusA
Read-only

Cache status of the cantonal GWR dumps (graceful-degradation entry point).

Always returns an evaluable status — never silently empty records. If a source is unreachable, this tool tells you when data was last refreshed.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription
noteYes
dumpsYes
sourceNo
ttl_hoursYes
provenanceYes

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true. The description adds value by stating the tool never returns empty records and reports last refresh time, which is beyond what annotations provide. No contradictions.

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

Conciseness5/5

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

Two sentences, no wasted words. The key information is front-loaded and every sentence contributes meaning.

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

Completeness4/5

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

Given zero parameters and the existence of an output schema, the description adequately covers the tool's behavior and return value. It is sufficient for the agent to understand what to expect, though it doesn't detail the output structure.

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

Parameters4/5

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

No parameters exist, so the baseline is 4. The description correctly adds no parameter information since none are needed.

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

Purpose4/5

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

The description clearly states the tool shows cache status of GWR dumps with graceful degradation. It is distinct from sibling tools like lookup_dwellings which retrieve data. No explicit differentiation from siblings, but the purpose is clear.

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

Usage Guidelines3/5

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

The description implies usage for checking cache health even when sources are unreachable, but does not explicitly state when to use it over alternatives. It provides context but no exclusions or direct guidance.

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

explain_codeA
Read-only

Decode a GWR code value (e.g. GSTAT=1004, GKAT=1020) into human-readable labels.

Uses the official code table shipped with the dump (DE/FR/IT).

ParametersJSON Schema
NameRequiredDescriptionDefault
codeYes
cantonNozh
attributeYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
sourceNo
provenanceYes
explanationsYes

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the read-only nature is clear. The description adds value by specifying the source of the labels (official code table) and the supported languages (DE/FR/IT), going beyond what annotations provide.

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

Conciseness4/5

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

The description is very concise at two sentences, but the second sentence could be more structured or broken into bullet points for clarity. No superfluous information, but room for slight improvement.

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

Completeness3/5

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

Given the tool's moderate complexity (3 params, no enums) and the presence of an output schema, the description adequately covers the main purpose. However, it lacks explanation for the optional parameter and does not mention the output schema's structure, resulting in moderate completeness.

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

Parameters2/5

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

With 0% schema description coverage, the description bears the full burden of explaining parameters. It includes an example of 'attribute' and 'code' but does not describe the optional 'canton' parameter at all, leaving a gap in understanding.

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

Purpose5/5

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

The description clearly states the tool decodes GWR code values into human-readable labels, with a specific verb and resource. It provides an example of inputs (GSTAT=1004) and distinguishes itself from sibling tools that handle different tasks.

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

Usage Guidelines3/5

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

The description implies use for decoding codes from a specific code table, but does not explicitly state when to use this tool vs alternatives, nor does it mention any prerequisites or when not to use it. Sibling tools have different purposes, so some implicit differentiation exists.

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

lookup_dwellingsA
Read-only

List all dwellings (EWID) of a building from the daily cantonal dump.

Includes rooms, floor area, floor and status per dwelling.

ParametersJSON Schema
NameRequiredDescriptionDefault
egidYes
cantonNozh

Output Schema

ParametersJSON Schema
NameRequiredDescription
egidYes
countYes
sourceNo
dwellingsYes
provenanceYes

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true. The description adds context (data source 'daily cantonal dump' and included fields) but does not disclose behavior beyond that, such as error handling or permissions. No contradiction with annotations.

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

Conciseness4/5

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

The description is concise (two sentences) and front-loaded with the core action. However, it could be slightly more structured with bullet points for clarity.

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

Completeness3/5

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

For a read-only list tool with an output schema, the description adequately mentions included fields but omits explanation of the required 'egid' parameter and the default value for 'canton'. The data source reference is vague.

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

Parameters2/5

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

Schema description coverage is 0%, so the description should explain parameters. However, it does not mention 'egid' as building ID or 'canton''s role. It only references 'a building' implicitly, leaving parameter semantics unclear.

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

Purpose5/5

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

The description clearly states the tool's function: 'List all dwellings (EWID) of a building' and specifies included attributes (rooms, floor area, floor, status). This distinguishes it from sibling tools like new_construction or dump_status.

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

Usage Guidelines3/5

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

Usage is implied but not explicit. The description does not mention when to use this tool versus alternatives, nor does it provide conditions for appropriate use.

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

new_constructionB
Read-only

New residential construction per year for a municipality (existing buildings).

Returns buildings, dwellings and 4+ room dwellings per year — the 4+ room share is a proxy for family housing and thus for future pupil numbers. Municipality is identified by its BFS number (e.g. 261 = City of Zurich).

ParametersJSON Schema
NameRequiredDescriptionDefault
cantonNo
since_yearNo
municipality_bfsYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
sourceNo
per_yearYes
provenanceYes
since_yearYes
municipalityYes
total_dwellingsYes
family_share_pctYesShare of 4+ room dwellings — proxy for family housing
municipality_bfsYes
total_dwellings_4plus_roomsYes

TDQS

B3/5.0
Behavior3/5

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

Annotations already indicate readOnlyHint=true. Description adds context about the 4+ room share being a proxy for family housing, but does not disclose any additional behavioral traits such as data source, update frequency, or limitations.

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

Conciseness4/5

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

Description is two sentences, efficiently conveying core purpose and a key interpretation note. No redundancy or fluff.

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

Completeness3/5

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

With an output schema present, return value explanation is not needed. However, the description lacks usage context and does not fully cover parameters. Adequate but with gaps.

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

Parameters2/5

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

Schema description coverage is 0%. Description only explains municipality_bfs with an example. Parameters canton and since_year are not described at all, leaving their semantics unclear.

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

Purpose4/5

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

Description clearly states it returns annual new residential construction data for a municipality, including buildings, dwellings, and 4+ room dwellings. However, phrasing 'existing buildings' may cause confusion about whether it covers new construction or existing stock.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus siblings like lookup_dwellings or construction_pipeline. Does not mention alternatives or exclusions.

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. 5 tool updatesv0.1.0
    • First observedconstruction_pipeline
    • First observeddump_status
    • First observedexplain_code
    • First observedlookup_dwellings
    • First observednew_construction

TDQS

A3.6/5.0

Scored across 5 tools

Disambiguation5/5

Each tool targets a distinct aspect: listing dwellings, historical construction, pipeline, code explanation, and cache status. There is no overlap or ambiguity in their purposes.

Naming Consistency3/5

Tool names mix patterns: verb_noun (lookup_dwellings, explain_code), adjective_noun (new_construction), and noun_noun (construction_pipeline, dump_status). While readable, the lack of a uniform pattern reduces consistency.

Tool Count5/5

Five tools is well-scoped for a niche domain like Swiss housing data. Each tool serves a clear function without excess or deficiency.

Completeness4/5

The tools cover current dwelling data, historical construction, future pipeline, code decoding, and system status. A minor gap is the lack of a dedicated building-level query beyond dwellings, but the set supports the stated planning use case.

Maintenance

ActivityActive
ResponsivenessNo issues

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