mcp-livedatapro

getCommercialRealEstate

Available retail, office, and industrial warehouse spaces, NNN lease rates per sqm, and vacancy rates. Use when searching for commercial business properties (office, retail, industrial warehouse, hospitality), NNN annual lease rates per sqm, cap rates, and available commercial units. Do not use for residential housing prices or apartments (use getRealEstateStats) or municipal zoning rules (use getParcelZoningInfo).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "city_or_postcode": "<city_or_postcode>",
      "property_type": "<property_type>"
    },
    "name": "getCommercialRealEstate"
  }
}

Input Schema

Name	Required	Description	Default
`property_type`	Yes	Commercial real estate asset classification (defaults to 'office').	office
`city_or_postcode`	Yes	Target city name, commercial business district, or postal code.

Schema Changelog

Changes observed during successful MCP inspections.

Changed6 schema fields changedOct 24, 2026
- addedInput schema / additionalProperties
```
Added value: +false
```
- addedInput schema / properties / city_or_postcode / examples
```
Added value: +[
+  "London Canary Wharf"
+]
```
- addedInput schema / properties / city_or_postcode / minLength
```
Added value: +2
```
- addedInput schema / properties / property_type / default
```
Added value: +"office"
```
- addedInput schema / properties / property_type / enum
```
Added value: +[
+  "retail",
+  "office",
+  "warehouse_industrial",
+  "hospitality"
+]
```
- addedInput schema / properties / property_type / examples
```
Added value: +[
+  "warehouse_industrial"
+]
```

Changed2 schema fields changedOct 24, 2026

changedInput schema / properties / city_or_postcode / description

Previous value: -"Target city, district, or postal code"New value: +"Target city name, commercial business district, or postal code."

changedInput schema / properties / property_type / description

Previous value: -"Commercial asset class"New value: +"Commercial real estate asset classification (defaults to 'office')."

First observedOct 21, 2026

TDQS

A4.1/5.0

Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the data semantics well (NNN annual rates per sqm, vacancy and cap rates), but omits currency, geographic coverage, data freshness/source, and whether the results are listings versus aggregates — meaningful gaps for a no-annotation data tool.

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?

Two sentences, front-loaded with the data payload and then the routing guidance. There is some redundancy — retail/office/industrial is listed twice and cap rates appear only in the second sentence — that trims a point off perfect concision.

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?

With only two fully documented parameters, no annotations, and no output schema, the description supplies enough to call the tool correctly and enough to know what comes back (rates, vacancy, cap rates). Currency, coverage area, and data freshness remain unstated but are secondary for a lookup of this simplicity.

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

Parameters3/5

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

Schema description coverage is 100% and the enum plus examples fully document property_type and city_or_postcode. The description adds nothing parameter-specific beyond echoing the asset classes already enumerated, so the baseline 3 is appropriate.

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 names the specific resource (available retail, office and industrial warehouse space) and the specific data returned (NNN lease rates per sqm, vacancy rates, cap rates). It also explicitly names the sibling tools it is not (getRealEstateStats for residential, getParcelZoningInfo for zoning), so an agent can distinguish it without opening a schema.

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?

It states an explicit trigger ("Use when searching for commercial business properties...") and an explicit exclusion with named alternatives for both residential housing and municipal zoning. Both the when and the when-not are covered, which is the top of the scale.

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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