GUTHMANN® Berlin Real Estate

Berlin real estate for AI agents: granular market data and property search, free, by GUTHMANN®.

CommunityOnlineNo sign-inGlobalFreeRead-only

What it can do

    What data it sees

    Do you need an account

    No: the server works without sign-in

    Berlin real estate for AI agents: granular market data and property search, free, by GUTHMANN®.

    How to connect

    How to connect GUTHMANN® Berlin Real Estate to Claude

    The server address to paste into Claude settings:

    https://mcp.guthmann.estate/mcp

    1. Open Claude (claude.ai or the desktop app).
    2. Go to Settings → Connectors.
    3. Click Add custom connector.
    4. Paste the server address copied below into Remote MCP server URL and click Add.
    5. In a chat, click + → Connectors and switch the new connector on.

    Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

    Authorization

    After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

    How to connect GUTHMANN® Berlin Real Estate to ChatGPT

    The server address to paste into ChatGPT settings:

    https://mcp.guthmann.estate/mcp

    1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
    2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
    3. Open Settings → Connectors and click Create.
    4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
    5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
    6. In a new chat open + → Apps/Connectors and enable the connector.

    OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

    Authorization

    On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

    How to connect GUTHMANN® Berlin Real Estate to Cursor

    The server address to paste into Cursor settings:

    https://mcp.guthmann.estate/mcp

    Fastest: click Open in Cursor below and confirm the prompt.

    Manually:

    1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
    2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
    3. Save the file. The server appears in the MCP list; authorize it there if asked.

    Authorization

    If the service needs sign-in, an authorize button appears next to the server in the MCP list.

    Server tool list (37)

    Raw names from tools/list. Only developers need these.

    berlin_boroughsReturns all 12 Berlin boroughs (Bezirke) with IDs and names. Key response fields: array of { bezirk_id, bezirk_name } - bezirk_id: 2 digits ("01" to "12") - bezirk_name: e.g. "Mitte", "Friedrichshain-Kreuzberg", "Pankow" Use when: - You need an overview of Berlin's administrative structure - You need a bezirk_id for market data queries Do NOT use when: - You already know the bezirk_id → use berlin_borough_details directly
    berlin_borough_detailsReturns details for one Berlin borough (Bezirk) by ID, optionally with all its districts. Parameters: - bezirk_id (required): 2-digit ID ("01" to "12") - ortsteile: "true" to include all districts of the borough Key response fields: { bezirk_id, bezirk_name, ortsteile?: [...] } (ortsteile = districts) Example: bezirk_id="03" → Pankow with 13 districts (Prenzlauer Berg, Weißensee, etc.)
    berlin_districtsReturns all 96 Berlin districts (Ortsteile), optionally filtered by borough. Parameters: - bezirk_id (optional): filter to the districts of one borough - bezirke: "true" to include borough references Key response fields: array of { ortsteil_id, ortsteil_name, bezirk_id?, bezirk_name? } - ortsteil_id: 4 digits (e.g. "0301" for Prenzlauer Berg) Examples of well-known districts: - Prenzlauer Berg (0301), Kreuzberg (0201), Mitte (0101) - Charlottenburg (0401), Neukölln (0801), Friedrichshain (0202)
    berlin_district_detailsReturns details for one Berlin district (Ortsteil) by ID, optionally with its neighborhoods. Parameters: - ortsteil_id (required): 4-digit ID (e.g. "0301") - planungsraeume: "true" to include all neighborhoods of the district Key response fields: { ortsteil_id, ortsteil_name, bezirk_id, bezirk_name, planungsraeume?: [...] } (planungsraeume = neighborhoods)
    berlin_neighborhoodsReturns all 542 Berlin neighborhoods (LOR Planungsräume), optionally filtered by borough or district. Parameters: - bezirk_id (optional): filter by borough - ortsteil_id (optional): filter by district - bezirke/ortsteile: "true" to include parent references Key response fields: array of { planungsraum_id, planungsraum_name, ... } - planungsraum_id: 8 digits (e.g. "03010101") Neighborhoods are the finest statistical level in Berlin. Ideal for granular market analyses.
    berlin_neighborhood_searchSearches Berlin neighborhoods (LOR Planungsräume) by name. Parameters: - q (required): search term (min. 3 characters) - limit: max. results (default: 25) - bezirk_id/ortsteil_id: optional filters to narrow the search Example: q="Kollwitz" finds the "Kollwitzplatz" neighborhood
    berlin_neighborhood_detailsReturns details for one Berlin neighborhood (LOR Planungsraum) by ID, optionally with its blocks. Parameters: - planungsraum_id (required): 8-digit ID - bloecke: "true" to include all blocks of the neighborhood Key response fields: { planungsraum_id, planungsraum_name, bezirk_id, bezirk_name, ortsteil_id, ortsteil_name, bloecke?: [...] } (bloecke = blocks)
    berlin_conservation_areasBerlin social conservation areas (Milieuschutzgebiete, §172 BauGB). 124 areas in 6 categories with polygon geometry. Parameters: - kategorie_id: filter by category ("erhaltungsgebiet" | "erweiterung" | "aufstellungsbeschluss" | "untersuchungsgebiet" | "beobachtungsgebiet" | "aufgehoben") - erweiterungen: "true" to embed extensions as a nested array inside their main area - include: comma-separated geo attributes; available: "centroid". Polygons are provided as GeoJSON URLs in geometry_urls - lat/lon: WGS84 point lookup. Returns only areas containing the point (typically 0 or 1 match). lat and lon must be provided together. Key response fields: array of { id, name, kategorie_id, kategorie_name, parent_id, beschreibung (description), datum (date), flaeche_km2 (area in km²), geometry_urls, centroid?, erweiterungen? (extensions) } Use for: "Is this address in a social conservation area?" (with lat/lon), overview of all Milieuschutz areas.
    berlin_conservation_area_detailsReturns a single Berlin social conservation area (Milieuschutzgebiet) by ID. For main areas, associated extensions are embedded automatically. Parameters: - id (required): 12-character hex string (deterministic area ID) - include: comma-separated geo attributes; available: "centroid". Polygons are provided as GeoJSON URLs in geometry_urls Key response fields: { id, name, kategorie_id, kategorie_name, parent_id, beschreibung (description), datum (date), flaeche_km2 (area in km²), geometry_urls, centroid?, erweiterungen? (extensions) }
    market_berlin_apartmentsBerlin apartment market data (listings + transactions). Sources: listing/offer data (IMV) + transaction data from the Berlin committee of valuation experts (GAA, Gutachterausschuss). Parameters: - zeitraum: "jahr" (default) | "monat" | "quartal" (abgeschlossene Quartale) - jahr: transaction data (GAA) + listing data (IMV), finest level: block - monat: listing data (IMV) only, finest level: District (Ortsteil) - quartal: listing data (IMV) only, closed quarters, finest level: District (Ortsteil) - rbs: spatial aggregation level — bezirk = Borough, ortsteil = District, planungsraum = Neighborhood (LOR Planungsraum) - For zeitraum=jahr: "stadt" | "bezirk" | "stadtteil" | "ortsteil" | "planungsraum" | "block" - For zeitraum=monat or quartal: "stadt" | "bezirk" | "stadtteil" | "ortsteil" Time filters: - start/end: flexible date values (YYYY, YYYY-MM, YYYY-MM-DD) - recent: number of most recent periods (alternative to start/end) Additional filters: - bezirk_id, stadtteil_id, ortsteil_id, planungsraum_id, block_id - baualtertyp: "neubau" (new construction) | "bestand" (existing stock) - limit, fields, include: "metadata" Key response fields (depending on zeitraum): - zeitraum=jahr: transaktionspreis_m2 (transaction price per m²), anzahl_transaktionen (number of transactions), kaufangebotspreis_m2 (asking sale price per m²), mietangebotspreis_m2 (asking rent per m²) - zeitraum=monat: kaufangebotspreis_m2, anzahl_kaufangebote (number of sale listings), kaufangebot_vermarktungszeit (time on market)
    market_berlin_apartment_buildingsBerlin apartment building market (rental buildings, "Zinshäuser") - transaction data. Source: transaction data from the Berlin committee of valuation experts (GAA, Gutachterausschuss). Parameters: - rbs: "stadt" | "bezirk" | "stadtteil" | "ortsteil" — bezirk = Borough, ortsteil = District Time filters: - start/end: flexible date values (YYYY, YYYY-MM, YYYY-MM-DD) - recent: number of most recent periods (alternative to start/end) Additional filters: - bezirk_id, stadtteil_id, ortsteil_id - limit, fields, include: "metadata" Key response fields: - transaktionspreis: average total purchase price (€) - transaktionen: number of transactions - vielfaches: purchase price multiplier (purchase price / annual net cold rent) - vielfaches_delta_*j: absolute change of the multiplier (1y, 5y, 10y, 15y) - transaktionspreis_m2: price per m² of living space Ideal for: investment market analysis, yield comparisons across locations
    market_germany_residentialNational market data for the German residential real estate market. Sources: DESTATIS, vdp, HYPOPORT. Includes price AND transaction indices for various market segments. Time filters: - start/end: flexible date values (YYYY, YYYY-MM, YYYY-MM-DD) - recent: number of most recent periods Response controls: - limit, fields, include: "metadata" Key response fields: PRICE INDICES: - preisindex_gesamt_destatis, preisindex_gesamt_vdp, preisindex_gesamt_hypoport (overall price index per source) - preisindex_grossstaedte_top_7 (top-7 major cities), preisindex_staedte_top_127 (top-127 cities) TRANSACTION INDICES: - transaktionsindex_grossstaedte_top_7, transaktionsindex_staedte_top_127
    market_germany_apartment_buildingsNational price index data for the German apartment building market. Source: vdp. Quarterly data for apartment buildings (rental buildings, "Mehrfamilienhäuser") across Germany. Time filters: - start/end: flexible date values (YYYY, YYYY-MM, YYYY-MM-DD) - recent: number of most recent periods (quarters) Response controls: - limit, fields, include: "metadata" Key response fields: - preisindex: price index for apartment buildings - preisindex_delta_1q: quarter-over-quarter change - preisindex_delta_1j: year-over-year change
    listingsThe GUTHMANN listings: the broker's active inventory in Berlin (for sale: owner-occupier apartments, investment apartments, apartment buildings, commercial). Every card carries its exposé URL on guthmann.estate. Addresses only for released listings, otherwise ZIP/District (Ortsteil)/Borough (Bezirk). Parameters: - segment: "APARTMENT_LIVING" | "APARTMENT_INVEST" | "APARTMENT_BUILDING" | "COMMERCIAL" - bezirk / ortsteil: name filter, e.g. "Pankow" / "Prenzlauer Berg" - preis_min / preis_max: purchase price in EUR - zimmer_min, flaeche_min: lower bounds for rooms / living area (m²) - locale: "de" | "en" for title, texts and exposé URL (default: en) - limit: 1-100 (default: 50) Key response fields: - public_id (key for listing_details), titel (title), teaser, expose_url - kaufpreis (purchase price), kaufpreis_pro_qm (price per m²), kaltmiete (net rent), bruttorendite (gross yield), mietfaktor (price-to-rent multiple) - wohnflaeche (living area), anzahl_zimmer (rooms), baujahr (construction year), energie_wertklasse (energy class) - bezirk (Borough), ortsteil (District), plz (ZIP), adresse (null when adresse_verborgen), bild (small first-party preview image, suitable for inline display)
    listing_detailsOne GUTHMANN listing in detail: prices and running costs, areas, amenities, energy certificate, exposé texts, images, contact and the exposé URL on guthmann.estate. When the address is not released, street/house number are null and the coordinate is deterministically offset by 150-300 m (koordinaten_versetzt = true). Parameters: - public_id: public listing id (hex, from listings or the exposé URL) - locale: "de" | "en" (default: en)
    macro_ecb_policy_ratesECB key interest rates. Source: Bundesbank. Parameters: - start/end: YYYY-MM-DD - recent: number of most recent periods - limit, fields, include: "metadata" Key response fields (German names): - zinssatz_hauptrefinanzierungssatz: main refinancing rate (the ECB's key rate) - zinssatz_einlagefazilitaet: deposit facility rate - zinssatz_spitzenrefinanzierungsfazilitaet: marginal lending facility rate
    macro_mortgage_lendingMortgage rates for residential housing loans. Source: Bundesbank. Parameters: - start/end: YYYY-MM-DD - recent: number of most recent periods - limit, fields, include: "metadata" Key response fields (German names): - zinssatz_gesamt: average rate across all fixed-interest periods - zinssatz_5_bis_10j: rate for 5-10 year fixed-interest periods - zinssatz_ueber_10j: rate for fixed-interest periods over 10 years - volumen_gesamt: new lending volume
    macro_bund_yieldsYields on German government bonds (Bunds). Source: Bundesbank. Parameters: - start/end: YYYY-MM-DD - recent: number of most recent periods - limit, fields, include: "metadata" Key response fields (German names): - rendite_10j: 10-year Bund yield - rendite_15j: 15-year Bund yield - rendite_30j: 30-year Bund yield
    macro_labor_unemploymentUnemployment statistics. Source: Bundesbank. Parameters: - start/end: YYYY-MM-DD - recent: number of most recent periods Key response fields (German names): - arbeitslose: registered unemployed (seasonally adjusted) - arbeitslosenquote: unemployment rate (%)
    macro_labor_employmentEmployment statistics. Source: Bundesbank. Parameters: - start/end: YYYY-MM-DD - recent: number of most recent periods Key response fields (German names): - erwerbstaetige: persons in employment (seasonally adjusted) - sv_beschaeftigte: employees subject to social insurance contributions - geringfuegig_beschaeftigte: marginally employed (mini-jobs)
    macro_labor_short_time_workShort-time work (Kurzarbeit) statistics. Source: Bundesbank. Parameters: - start/end: YYYY-MM-DD - recent: number of most recent periods Key response fields (German names): - kurzarbeiter: short-time workers (seasonally adjusted)
    macro_inflation_hicpInflation data (HICP - harmonized index of consumer prices). Source: Bundesbank. Parameters: - start/end: YYYY-MM-DD - recent: number of most recent periods Key response fields (German names): - hvpi_gesamt: overall HICP - hvpi_gesamt_ohne_energie_nahrungsmittel: core inflation (HICP excluding energy and food) - hvpi_energie, hvpi_nahrungsmittel, hvpi_dienstleistungen, hvpi_mieten: energy, food, services, rents
    macro_construction_pricesConstruction price index for residential buildings. Source: Bundesbank. Quarterly data (2015=100). Parameters: - start/end: YYYY-MM-DD - recent: number of most recent periods Key response fields (German names): - preisindex: construction price index - preisindex_delta_1q: change vs. previous quarter - preisindex_delta_1j: change vs. previous year
    macro_gdpGDP data (gross domestic product). Source: Bundesbank. Quarterly data, price-adjusted, seasonally and calendar-adjusted (2015=100). Parameters: - start/end: YYYY-MM-DD - recent: number of most recent periods Key response fields (German names): - kettenindex: GDP chain-linked index - kettenindex_delta_1q: change vs. previous quarter - kettenindex_delta_1j: change vs. previous year
    field_metadataReturns field definitions for interpreting API responses. Use this to understand fields, units, data types, and sources. Parameters: - domain (optional): specific domain for detailed field information - locale: "de" (default) | "en" Available domains: - berlin: geographic reference data — Boroughs (Bezirke), Districts (Ortsteile), Neighborhoods (LOR Planungsräume) - immobilienmarkt.berlin.wohnungen: Berlin apartment market - immobilienmarkt.berlin.mehrfamilienhaeuser: Berlin apartment buildings - makrooekonomie.kapitalmarkt: mortgage lending rates, Bund yields - makrooekonomie.geldpolitik: ECB policy rates - makrooekonomie.arbeitsmarkt: unemployment, employment Without a domain parameter: returns an overview of all available domains.
    socio_berlin_construction_activityConstruction activity data for Berlin. Source: Amt für Statistik Berlin-Brandenburg. Shows net changes: building balance, dwelling balance, living-space balance. Parameters: - rbs: "stadt" (city) | "bezirk" (Borough) | "stadtteil" | "ortsteil" (District) | "planungsraum" (Neighborhood, LOR Planungsraum) - bezirk_id, stadtteil_id, ortsteil_id, planungsraum_id: geographic filters - start/end: period (YYYY, YYYY-MM, YYYY-MM-DD) - recent: number of most recent periods - limit, fields, include: "metadata" Key response fields: - gebaeude_saldo: net change in number of buildings - wohnungen_saldo: net change in number of dwellings - wohnflaeche_m2_saldo: net change in living space (m²)
    socio_berlin_migration_externalExternal migration for Berlin: migration across the city boundary, annual, by nationality. Source: Amt für Statistik Berlin-Brandenburg. Parameters: - rbs: "stadt" (city) | "bezirk" (Borough) | "stadtteil" | "ortsteil" (District) | "planungsraum" (Neighborhood, LOR Planungsraum) - bezirk_id, stadtteil_id, ortsteil_id, planungsraum_id: geographic filters - staat_code: filter by country code (e.g. "000" for Germany) - alpha2: filter by ISO 3166-1 alpha-2 code (e.g. "TR") - start/end, recent, limit, fields, include: "metadata" Key response fields: - zuzuege: move-ins to Berlin - fortzuege: move-outs from Berlin - saldo: net migration (move-ins minus move-outs)
    socio_berlin_migration_matrixMigration matrix for Berlin: migration flows between areas (moves within Berlin, annual). The RBS level applies to both origin and destination. Source: Amt für Statistik Berlin-Brandenburg. Parameters: - rbs: "stadt" (city) | "bezirk" (Borough) | "stadtteil" | "ortsteil" (District) | "planungsraum" (Neighborhood, LOR Planungsraum) (default: bezirk) - von_rbs_id: filter by origin-area ID - nach_rbs_id: filter by destination-area ID - min_personen: lower bound on number of persons (default 1) - start/end, recent, limit, fields, include: "metadata" Key response fields: - von_rbs_id/von_rbs_name: origin area - nach_rbs_id/nach_rbs_name: destination area - anzahl_personen: number of moves
    socio_berlin_populationPopulation stock for Berlin (headline figures) at the Neighborhood level (LOR Planungsraum), semi-annual. Source: Amt für Statistik Berlin-Brandenburg. Parameters: - rbs: "stadt" (city) | "bezirk" (Borough) | "stadtteil" | "ortsteil" (District) | "planungsraum" (Neighborhood) - bezirk_id, stadtteil_id, ortsteil_id, planungsraum_id: geographic filters - start/end, recent, limit, fields, include: "metadata" Key response fields: - einwohner_gesamt (total population), einwohner_maennlich/_weiblich (male/female) - einwohner_deutsch/_auslaendisch (German/foreign nationals), einwohner_ohne/_mit_migrationshintergrund (without/with migration background) - frauen_anteil, auslaender_anteil, migrationshintergrund_anteil: shares of women, foreign nationals, migration background (0–1)
    socio_berlin_age_groupsBerlin population by 8 age groups, additionally by population group. Source: Amt für Statistik Berlin-Brandenburg. Parameters: - rbs: "stadt" (city) | "bezirk" (Borough) | "stadtteil" | "ortsteil" (District) | "planungsraum" (Neighborhood, LOR Planungsraum) - bevoelkerungsgruppe: "alle" (all) | "mit_migrationshintergrund" (with migration background) (optional) - altersgruppe: age group, e.g. "alter_unter_6", "alter_65_und_mehr" (optional) - bezirk_id, stadtteil_id, ortsteil_id, planungsraum_id: geographic filters - start/end, recent, limit, fields, include: "metadata" Key response fields: - bevoelkerungsgruppe_id/_name (population group), altersgruppe_id/_name (age group), anzahl_einwohner (number of residents)
    socio_berlin_originBerlin population with a migration background, by area of origin. Source: Amt für Statistik Berlin-Brandenburg. ⚠️ herkunft_ebene: "eu_gesamt" is the aggregate over the individual "eu_land" entries. The default (drittland,eu_gesamt,nicht_zuordenbar) prevents double-counting EU countries. Parameters: - rbs: "stadt" (city) | "bezirk" (Borough) | "stadtteil" | "ortsteil" (District) | "planungsraum" (Neighborhood, LOR Planungsraum) - herkunft_ebene: origin level, comma-separated, e.g. "drittland,eu_gesamt" (optional; default prevents double counting) - herkunftsgebiet: area of origin, e.g. "tuerkei", "ukraine", "eu" (optional) - top: top N areas of origin by count (optional) - bezirk_id, stadtteil_id, ortsteil_id, planungsraum_id: geographic filters - start/end, recent, limit, fields, include: "metadata" Key response fields: - herkunftsgebiet_id/_name (area of origin), herkunft_ebene (origin level), anzahl_einwohner_mit_migrationshintergrund (residents with a migration background)
    socio_berlin_census_dwellingsZensus 2022 dwelling stock data for Berlin. Source: Statistisches Bundesamt, Zensus 2022. Without a category: total number of dwellings. With a category: - raeume: breakdown by number of rooms - flaeche: breakdown by floor-area cluster (under 40 m², 40-59 m², etc.) - nutzung: breakdown by type of use (owner-occupied, rented, vacant) Parameters: - rbs: "stadt" (city) | "bezirk" (Borough) | "stadtteil" | "ortsteil" (District) | "planungsraum" (Neighborhood, LOR Planungsraum) - kategorie: "raeume" | "flaeche" | "nutzung" (optional) - bezirk_id, stadtteil_id, ortsteil_id, planungsraum_id: geographic filters - start/end, recent, limit, fields, include: "metadata"
    socio_berlin_census_vacancyZensus 2022 dwelling vacancy data for Berlin. Source: Statistisches Bundesamt, Zensus 2022. Breakdown by vacancy category (duration or reason). Parameters: - rbs: "stadt" (city) | "bezirk" (Borough) | "stadtteil" | "ortsteil" (District) | "planungsraum" (Neighborhood, LOR Planungsraum) - kategorie: "dauer" (duration) | "grund" (reason) (optional) - bezirk_id, stadtteil_id, ortsteil_id, planungsraum_id: geographic filters - start/end, recent, limit, fields, include: "metadata" Key response fields: - kategorie_id, kategorie_label: vacancy category - anzahl: number of vacant dwellings
    socio_berlin_census_rentsZensus 2022 rent data for Berlin. Source: Statistisches Bundesamt, Zensus 2022. Without a category: weighted average across all dwellings (net cold rent, net cold rent per m², count). With category "flaeche": rent per m² by floor-area cluster. Parameters: - rbs: "stadt" (city) | "bezirk" (Borough) | "stadtteil" | "ortsteil" (District) | "planungsraum" (Neighborhood, LOR Planungsraum) - kategorie: "flaeche" (optional) - bezirk_id, stadtteil_id, ortsteil_id, planungsraum_id: geographic filters - start/end, recent, limit, fields, include: "metadata" Key response fields: - nettokaltmiete: average net cold rent (EUR) - nettokaltmiete_m2: net cold rent per m² (EUR) - anzahl_wohnungen: number of dwellings
    socio_berlin_census_buildingsZensus 2022 building data for Berlin. Source: Statistisches Bundesamt, Zensus 2022. Without a category: total number of buildings. With a category: - bauweise: construction type (detached, row house, semi-detached) - eigentumsform: ownership type (private individual, cooperative, municipality) - heizungsart: heating type (central heating, per-floor heating, individual stoves) - energietraeger: energy source (gas, oil, district heating, electricity) Parameters: - rbs: "stadt" (city) | "bezirk" (Borough) | "stadtteil" | "ortsteil" (District) | "planungsraum" (Neighborhood, LOR Planungsraum) - kategorie: "bauweise" | "eigentumsform" | "heizungsart" | "energietraeger" (optional) - bezirk_id, stadtteil_id, ortsteil_id, planungsraum_id: geographic filters - start/end, recent, limit, fields, include: "metadata"
    socio_berlin_census_householdsZensus 2022 household data for Berlin. Source: Statistisches Bundesamt, Zensus 2022. Without a category: total number of households. With a category: - groesse: household size (1 person, 2 persons, etc.) - wohndauer: length of residence (under 1 year, 1-5 years, etc.) Parameters: - rbs: "stadt" (city) | "bezirk" (Borough) | "stadtteil" | "ortsteil" (District) | "planungsraum" (Neighborhood, LOR Planungsraum) - kategorie: "groesse" | "wohndauer" (optional) - bezirk_id, stadtteil_id, ortsteil_id, planungsraum_id: geographic filters - start/end, recent, limit, fields, include: "metadata"
    searchSemantic search over guthmann.estate — market insights, reports, neighborhood portraits, listing exposés, project pages and the company's own pages. Hybrid retrieval (vector + keyword, no reranking); one result per page with title, description, image, best-matching snippet and score. Use it for questions that need prose (analysis, context, advice); use the data tools for exact numbers and `listings` for what is currently for sale — the search index follows the website with up to six hours of delay. Parameters: - q: natural-language query, in the language of the pages you want (min 2 characters) - locale: "de" | "en" — language of the indexed pages (default: en) - section: comma-separated filter — "listings" (exposés), "projects" (new-build projects), "market-intelligence" (insights, reports, portraits), "pages" (company, services, guides); omit for all - limit: 1-20 pages (default: 10) Key response fields: - url, title, description, image, section, language - snippet (best-matching text passage), score (0-1)