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Search Address

search_address

Turn a postal address typed as free text into cadastral parcels, ranked by confidence (0 to 1; 0.75 or more means the house number and the municipality match). Spain (default, CartoCiudad; Basque Country and Navarre entrances come back with country ES and their foral reference) and 26 more countries: FR, IT, DE (not Bavaria), AT, NL, BE, PL, CH, CZ, DK, NO, FI, EE, LV, LT, SI, SK, BG, GR, CY, LU, LI, IS, IE, UK (Scotland only) and PT (not Lisbon, Porto or Coimbra). Sweden and Croatia answer CNV_COVERAGE. Include the street number and the municipality or postcode, e.g. 'Calle Gran Via 31, Madrid' or '8 boulevard du Port, Amiens'. In Spain the 14-character reference is the building (finca): call get_units for its dwellings or get_parcel for the outline. Costs 1 quota unit when it returns candidates; misses are free.

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum candidates (1-10, default 5)
addressYesFree-text address: street and number, then municipality and/or postcode
countryNoCountry of the address. Default ES (also returns Basque Country and Navarre).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so: it discloses coverage limits per country (DE not Bavaria, UK Scotland only, PT excludes Lisbon/Porto/Coimbra), the CNV_COVERAGE outcome for Sweden and Croatia, the ES handling of Basque Country and Navarre, and the cost model ('1 quota unit when it returns candidates; misses are free'). These are exactly the non-obvious traits an agent cannot infer from the schema.

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?

Purpose and confidence semantics are front-loaded, and every sentence is informational. The 27-country enumeration is long and largely mirrors the country enum already present in the schema, so that run of text is the least efficient part, though the inline caveats partly justify it.

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?

No output schema exists, and the description compensates well by explaining ranking, the confidence scale, the 14-character Spanish reference meaning, and the next tools to call. It stops short of describing the actual response fields (parcel reference, coordinates, address components), which is the remaining gap for a no-output-schema tool.

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 schema already documents all three parameters and the baseline is 3. The description earns a bump by adding format guidance for 'address' beyond the schema's one-liner (street + number, then municipality and/or postcode, with examples) and by restating the default country plus its regional exceptions.

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 specific verb and resource: turn free-text postal address into cadastral parcels ranked by confidence. It also defines the confidence scale semantics (>=0.75 means house number and municipality match), which lets an agent judge result quality without opening anything else.

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?

Gives concrete input requirements ('include the street number and the municipality or postcode') with two worked examples, and routes the follow-up step clearly: 'call get_units for its dwellings or get_parcel for the outline'. It does not, however, say when to prefer this over siblings like resolve_reference or list_streets when those might also fit.

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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