ENTIA Entity Verification MCP

Zone Profile

zone_profile

Read-onlyIdempotent

Socioeconomic profile of a Spanish postal code — 17 blocks: income, employment, demographics, business census, real estate, FTTH, poverty, tourism.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`postal_code`	Yes	Spanish 5-digit postal code (28013 = Madrid Gran Vía)

Output Schema

TableJSON Schema

Name	Required	Description	Default
`_meta`	No
`economy`	No
`province`	No
`income_aeat`	No
`postal_code`	No
`real_estate`	No
`municipality`	No
`employment_sepe`	No
`businesses_dirce`	No
`demographics_ine`	No
`autonomous_community`	No
`entia_classification`	No
`digital_infrastructure`	No
`poverty_inequality_ccaa`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 14, 2026
- changedInput schema / properties / postal_code / pattern
```
Previous value: -"^[0-9]{5}$"New value: +"^[0-9]{4,5}$"
```

Changed1 schema field changedAug 18, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "description": "Socioeconomic profile of a Spanish postal code, 17 blocks from official sources.",
+  "properties": {
+    "_meta": {
+      "type": "object"
+    },
+    "autonomous_community": {
+      "type": "string"
+    },
+    "businesses_dirce": {
+      "type": "object"
+    },
+    "demographics_ine": {
+      "type": "object"
+    },
+    "digital_infrastructure": {
+      "type": "object"
+    },
+    "economy": {
+      "type": "object"
+    },
+    "employment_sepe": {
+      "type": "object"
+    },
+    "entia_classification": {
+      "type": "object"
+    },
+    "income_aeat": {
+      "type": "object"
+    },
+    "municipality": {
+      "type": "string"
+    },
+    "postal_code": {
+      "type": "string"
+    },
+    "poverty_inequality_ccaa": {
+      "type": "object"
+    },
+    "province": {
+      "type": "string"
+    },
+    "real_estate": {
+      "type": "object"
+    }
+  },
+  "type": "object"
+}

Changed9 schema fields changedMay 26, 2026

removedInput schema / additionalProperties
```
Removed value: -false
```

removedInput schema / properties / cp

Removed value: -{
-  "anyOf": [
-    {
-      "type": "string"
-    },
-    {
-      "type": "null"
-    }
-  ],
-  "default": null,
-  "description": "Alias for postal_code — pass here if your client serializes 'cp' instead of 'postal_code'"
-}

removedInput schema / properties / postal_code / anyOf

Removed value: -[
-  {
-    "type": "string"
-  },
-  {
-    "type": "null"
-  }
-]

removedInput schema / properties / postal_code / default
```
Removed value: -null
```

changedInput schema / properties / postal_code / description

Previous value: -"Spanish postal code (5 digits, e.g. 28001, 08001, 41001)"New value: +"Spanish 5-digit postal code (28013 = Madrid Gran Vía)"

addedInput schema / properties / postal_code / pattern
```
Added value: +"^[0-9]{5}$"
```
addedInput schema / properties / postal_code / type
```
Added value: +"string"
```
addedInput schema / required
```
Added value: +[
+  "postal_code"
+]
```

changedOutput schema / (root)

Previous value: -{
-  "additionalProperties": true,
-  "type": "object"
-}New value: +null

First observedMay 3, 2026

TDQS

A3.6/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is fully covered by structured data. The description adds useful context about the breadth of returned data (17 blocks), but discloses nothing about data freshness, coverage limits, or how unknown postal codes are handled.

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?

A single, front-loaded sentence that wastes no words: it leads with the resource and scope, then lists contents. Nothing is redundant with the title or schema.

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 an output schema present, the description need not explain return values, and it helpfully previews the 17 blocks. For a one-parameter read-only tool this is nearly complete; only the absence of any routing guidance to sibling tools keeps it short of a 5.

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 single parameter is well documented in the schema, including the pattern and a Madrid example. The description adds no further parameter meaning, so the baseline 3 applies.

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 a specific resource (socioeconomic profile) and its scope (a Spanish postal code), then enumerates the 17 content blocks it returns. This clearly distinguishes it from sibling tools like entity_lookup, professional_lookup, and run_risk_audit, which operate on entities rather than geographic zones.

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

Usage Guidelines2/5

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

The description says what the tool returns but never states when to reach for it instead of alternatives such as get_full_dossier or run_risk_audit, nor any prerequisites or exclusions. Usage is only inferable from the fact that it takes a postal code.

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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