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cenogram-mcp-server

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compare_locations

Read-only

Compare real estate transaction statistics across multiple Polish districts side-by-side, including median price per m², average area, and transaction counts.

Instructions

Compare real estate statistics across multiple locations side-by-side. Provide 2-5 district names to compare median price/m², average area, and transaction counts. Use list_locations first to find valid location names. Requires at least one filter besides districts (e.g., propertyType). Example: compare Mokotów, Wola, Ursynów for apartments. Note: median/average prices are market-based — fractional ownership shares and non-market deeds (public tenders, foreclosures, privileged/subsidized sales) are excluded from price aggregates. Transaction counts and coverage stay complete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
floorNoFloor of the unit (piętro lokalu, residential). Multi-select buckets: exact integers incl. '0' (parter) and negatives e.g. '-1' (basement), 'Nplus' e.g. '10plus' = 10 or more, '0plus' = ground and above, 'unknown' = no floor recorded (NULL). E.g. ['0','1','2'] for ground-to-2nd floor. Building storeys are a different attribute. Without 'unknown', rows with no floor are excluded.
roomsNoNumber of rooms (izby) filter, residential units only. Multi-select; '8plus' means 8 or more, 'unknown' = no room count recorded (NULL). E.g. ['2','3'] for 2-3 izby flats. Without 'unknown', rows with no room count are excluded.
dateToNoEnd date (YYYY-MM-DD)
streetNoStreet name filter
maxAreaNoMaximum area in m²
minAreaNoMinimum area in m²
dateFromNoStart date (YYYY-MM-DD)
maxPriceNoMaximum price in PLN
minPriceNoMinimum price in PLN
districtsYesComma-separated district names to compare (2-5, must be unique). E.g. 'Mokotów,Wola,Ursynów'
marketTypeNoMarket type filter
buildingTypeNoBuilding type filter (PKOB classification). 'unknown' = no type recorded (NULL); without it such rows are excluded (~39% of buildings have no type).
propertyTypeNoProperty type filter (recommended - API requires at least one filter)
unitFunctionNoUnit/apartment function filter. 'unknown' = no function recorded (NULL); without it such rows are excluded. Garages appear only when 'garage' is selected, not via 'unknown'.
ownershipTypeNoOwnership / legal-right type filter (rodzaj prawa do nieruchomości). land_ownership; perpetual_usufruct (użytkowanie wieczyste — covers both registry codes for this right); cooperative_ownership; unit_sale; ownership; unit_ownership_with_appurtenant_right; building_ownership_with_appurtenant_right. 'unknown' = no right recorded (NULL). Multi-select; e.g. ['land_ownership','perpetual_usufruct'] to compare ownership vs perpetual usufruct on undeveloped land.
mpzpDesignationNoMPZP zoning designation prefix filter (e.g. 'terenRolniczy', 'budownictwoMieszkanioweJednorodzinne', 'budownictwoMieszkanioweWielorodzinne'). Use 'unknown' for rows with no designation recorded (NULL); distinct from the registry code 'brakMPZPLubWZ'.
transactionTypeNoTransaction type filter. For market analysis, ALWAYS specify to exclude non-market transactions.
includeDemographicsNoAdd a GUS BDL demographics block per district (county-level: population density, wages, unemployment, median age, plus a few cross-source ratios like price-to-income). Districts that don't resolve to a county are omitted from the demographics section.
Behavior4/5

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

Annotations declare readOnlyHint=true and destructiveHint=false. The description adds behavioral context: fractional ownership and non-market deeds are excluded from price aggregates, but transaction counts remain complete. This goes beyond annotations by clarifying data filtering.

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 a single, well-structured paragraph with no wasted words. It efficiently covers purpose, prerequisites, example, and a behavioral note. The key action is front-loaded.

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 the tool's 18 parameters and no output schema, the description adequately covers the main purpose, required inputs, and a behavioral exclusion. It hints at output metrics (median, average, counts), which is sufficient for tool selection.

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?

Schema description coverage is 100%, so the schema provides detailed parameter info. The description adds value by noting the districts parameter requires 2-5 unique names, and that an additional filter (e.g., propertyType) is needed. This aids correct invocation.

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 verb 'compare' and resource 'real estate statistics across multiple locations side-by-side'. It specifies the output metrics (median price/m², average area, transaction counts) and differentiates from siblings like list_locations or get_market_overview by requiring 2-5 districts and an extra filter.

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

Usage Guidelines4/5

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

The description explicitly instructs to use list_locations first, requires at least one filter besides districts, and provides an example. While it does not explicitly state when not to use, the context implies it is for multi-location comparison, not single-location stats.

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

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