Spain Open Data MCP

Household income

income

Read-onlyIdempotent

Fetch household earnings data for Spanish places from INE's atlas, down to census tract, with pay, inequality, trends, and regional benchmarks for purchasing power. Compare districts.

Instructions

Household income for a place in Spain from INE's income atlas, down to census tract.

Returns net and gross income per person and per household, mean and median per consumption unit, inequality (Gini, P80/P20), income sources (wages, pensions, benefits), a trend, and benchmarks against the province, region and Spain. Use it for purchasing power, price positioning and choosing between districts. Figures are euros of the data year; the atlas runs about two years behind.

Input Schema

Name	Required	Description	Default
`place`	Yes	Place name or INE code: municipality ('Valladolid' or '47186'), province ('41'; a bare name like 'Sevilla' means the city), autonomous community ('Cataluña' or 'CA09'), district ('4718603') or census tract ('4718603012'). 'Name, Province' picks between same-named towns.
`years`	No	Years of history for the trend (max 9).
`rank_by`	No	Metric used to rank sub-areas.	net_income_per_person
`sub_areas`	No	For a municipality, rank its 'district's or census 'tract's. Default 'none'.	none

Output Schema

Name	Required	Description
`data`	Yes
`checks`	No
`sources`	Yes
`confidence`	Yes	Lowest confidence across inputs: high, medium or low. Never state a conclusion more strongly than this.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv0.1.1Oct 17, 2026

addedOutput schema / $defs / Place / properties / official_name

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "INE's form of the name when it differs ('Palmas de Gran Canaria, Las').",
+  "title": "Official Name"
+}

First observedv0.1.0Oct 16, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare the safe read-only, idempotent profile, so the bar is lower. The description adds meaningful context beyond them: the data lag (~two years behind), that figures are euros of the data year, and the benchmark scope (province, region, Spain). It doesn't discuss pagination or output shape, but with annotations and an output schema those matter less.

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?

Front-loads the core identity (income for a place, source, granularity) in the first sentence, then enumerates returns and use cases without waste. Dense but every clause earns its place.

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?

With an output schema present, return values need no prose explanation, and the description still covers source, granularity, benchmark scope and a key freshness caveat. Nothing an agent needs to call it correctly is missing.

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%, so the schema already fully documents place, years, rank_by and sub_areas with enum values. The description touches the trend and sub-area ranking conceptually but adds no syntax or format detail beyond the schema, so 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?

States a specific verb+resource (household income for a place in Spain) with source (INE income atlas) and resolution (down to census tract). It clearly distinguishes from siblings like rents, crime or demographics by naming the exact dataset and granularity.

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 explicit use cases (purchasing power, price positioning, choosing between districts), which tells the agent when this tool is appropriate. However, it never names an alternative sibling (e.g., compare_areas or rents) or draws an exclusion boundary, so it falls short of a 5.

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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