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Get Zonal Price Distribution

get_zonal_price_distribution

Read-only

Map and rank median price per m² by postal code or commune across a city or department, from recorded DVF sales. Hosts with MCP Apps support (such as ChatGPT and Claude) render the result as an interactive price map; other clients get the same data as JSON.

REQUIRED: At least one scope filter:

code_departement: Department code (e.g., "75" for Paris)
commune: Major city (e.g., "PARIS" - returns all arrondissements)

Optional:

type_local: "Maison" or "Appartement"
group_by: "code_postal" (default) or "commune"
min_transactions: Minimum transactions to include zone (default: 10)
date_debut/date_fin: Date range (default: last year)

Returns per zone:

Centroid coordinates (lat/lon) for map plotting
Median and average price/m²
Transaction count
Relative position: "expensive", "average", or "affordable"

Use this when the user wants to: map or compare prices across arrondissements, postal codes or communes, or find the most/least expensive zones.

Example: Paris zones by postal code: {commune: "PARIS", type_local: "Appartement"}

Cost: 15 credits per call

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_zonal_price_distribution"
  }
}

Input Schema

Name	Required	Description	Default
`commune`	No	Major city name (e.g., 'PARIS' - returns all arrondissements)
`date_fin`	No	End date (default: today)
`group_by`	No	Aggregation level (default: code_postal)	code_postal
`date_debut`	No	Start date (default: 1 year ago)
`type_local`	No	Property type filter
`code_departement`	No	Department code (e.g., '75')
`min_transactions`	No	Minimum transactions to include a zone (default: 10)

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 24, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, destructiveHint=false and openWorldHint=false, so the description is not required to establish safety. It still adds real value by disclosing client-dependent rendering (interactive map vs. JSON), credit cost (15 per call), and default date/min_transactions behavior. It stops short of describing pagination or limits on returned zones.

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?

Front-loads the core action, then organizes requirements, options, and returns into scannable blocks with an example and cost line. The parameter list partially repeats the schema, so it is slightly longer than strictly necessary, but every block is usable.

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

Completeness5/5

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

For a 7-parameter analytics tool with no output schema, the description documents the per-zone return fields (centroid, median/average, transaction count, relative position), defaults, cost, and rendering behavior. An agent has everything needed to call it and describe the result.

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 coverage is 100%, so the baseline is 3, but the description adds interpretive meaning: that commune='PARIS' returns all arrondissements, that group_by controls aggregation level, and that a date range defaults to the last year. Most individual field descriptions still duplicate the schema, keeping it below 5.

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?

States a precise verb+resource: 'Map and rank median price per m² by postal code or commune across a city or department, from recorded DVF sales.' The spatial/zonal aggregation scope and map output clearly separate it from point-estimate or transaction-search siblings.

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

Usage Guidelines5/5

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

Includes an explicit 'Use this when the user wants to: map or compare prices across arrondissements, postal codes or communes, or find the most/least expensive zones,' plus a required-scope constraint ('At least one scope filter') and a worked example. It does not name a sibling as an alternative, but the selection condition is unambiguous.

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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