# Spain Open Data (pypi · spain-open-data-mcp)

Market sizing, prices, rents, crime and locations in Spain from INE and other public data

- Trust score: 81/100 (high trust)
- Change this week: 0
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-10-25

## Components

- remote · `spain-open-data-mcp-165703905656.europe-west1.run.app`: 75/100, [markdown](https://verifymcp.io/servers/digvijaysingh-ai-spain-open-data-mcp/spain-open-data-mcp-165703905656.md), [page](https://verifymcp.io/servers/digvijaysingh-ai-spain-open-data-mcp/spain-open-data-mcp-165703905656)
- pypi · `spain-open-data-mcp`: 81/100 (this document), [markdown](https://verifymcp.io/servers/digvijaysingh-ai-spain-open-data-mcp/spain-open-data-mcp.md), [page](https://verifymcp.io/servers/digvijaysingh-ai-spain-open-data-mcp/spain-open-data-mcp)

## Channel facts

- Registry: `pypi`
- Package: `spain-open-data-mcp`
- Version: `0.1.4`
- Transport: `stdio`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-10-25.

- **Supply Chain Security**: 100/100
  - No malware found by supply-chain analysis.
  - No known CVEs affecting this package version or its production dependencies.
  - Runs uv_build at install time, a recognised build step with no custom scripting around it.
  - 2 of 44 dependencies flagged as unhealthy.
- **Provenance & Transparency**: 97/100
  - Source repository is publicly reachable at the declared URL.
  - Cryptographically verified build provenance (signed, bound to digvijaysingh-ai/spain-open-data-mcp).
  - Clear OSI-approved license (MIT).
  - Actively maintained (last published 7 days ago).
  - Disclosure check failed: no security disclosure policy was found in the source repository.
- **Schema Quality & AI Usability**: 76/100
  - 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).
  - AI-judged instruction clarity (excellent).
  - Context-footprint check failed: tool/resource definitions use about 3543 tokens (~236/item across 15 items; 13 tools + 2 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 0/100
  - Stability not yet verified: not enough scan history yet (needs a 30-day window).
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% of tool parameters carry a description.
  - Structured output schemas are declared (100% of tools); any adoption earns full credit.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - We read all 13 captured tool definition(s), and no name or description among them implies an irreversible operation.
  - An AI judge read all 15 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 100/100
  - Implements a current MCP spec version (2026-07-28).

**Unverified: 1 category.** A category scored 0 because we could not verify it: a data source with nothing on this package, evidence we could not reach, or a check we could not run. We only credit what we can confirm.

## Install

### How do I install the Spain Open Data MCP server?

Spain Open Data runs locally as a PyPI package, launched with uvx spain-open-data-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

### Claude

```bash
claude mcp add digvijaysingh-ai-spain-open-data-mcp -- uvx spain-open-data-mcp
```

### Cursor

```json
{
  "mcpServers": {
    "digvijaysingh-ai-spain-open-data-mcp": {
      "command": "uvx",
      "args": [
        "spain-open-data-mcp"
      ]
    }
  }
}
```

### VS Code

```json
{
  "servers": {
    "digvijaysingh-ai-spain-open-data-mcp": {
      "command": "uvx",
      "args": [
        "spain-open-data-mcp"
      ]
    }
  }
}
```

### Codex

```bash
codex mcp add digvijaysingh-ai-spain-open-data-mcp -- uvx spain-open-data-mcp
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "digvijaysingh-ai-spain-open-data-mcp": {
      "type": "local",
      "command": [
        "uvx",
        "spain-open-data-mcp"
      ],
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add digvijaysingh-ai-spain-open-data-mcp --command uvx --arg spain-open-data-mcp
```

### Hermes

```yaml
mcp_servers:
  digvijaysingh-ai-spain-open-data-mcp:
    command: "uvx"
    args: ["spain-open-data-mcp"]
```

### Netclaw

```json
{
  "McpServers": {
    "digvijaysingh-ai-spain-open-data-mcp": {
      "Transport": "stdio",
      "Command": "uvx",
      "Arguments": [
        "spain-open-data-mcp"
      ]
    }
  }
}
```

### Vellum

```bash
assistant mcp add digvijaysingh-ai-spain-open-data-mcp -t stdio -c uvx -a spain-open-data-mcp
```

### Other

```json
{
  "mcpServers": {
    "digvijaysingh-ai-spain-open-data-mcp": {
      "command": "uvx",
      "args": [
        "spain-open-data-mcp"
      ]
    }
  }
}
```

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-10-18 (score 81, +15)

- [security improvement] Malware scan: unverified → pass

### 2026-10-17 (score 66)

First indexed and scored.

## MCP tools (13)

### `resolve_place` (~189 tokens)

Resolve a Spanish place

Find the INE code and level (CCAA, province, municipality, district, tract) for a place in Spain.

Use this first when a question names a place. Returns the best match first, with
alternatives (e.g. 'Valencia' is both a city and a province). Handles accents, Basque,
Catalan and Galician names, and common English names (Seville, Catalonia).
Districts and tracts are shown with the OpenStreetMap neighbourhood names inside them
('Valladolid distrito 10 (Parquesol, Girón, La Victoria)'), and a neighbourhood name
('Parquesol, Valladolid', 'Gràcia, Barcelona') returns the INE district that contains it.

Input parameters:

- `query` (string, required): Place name or INE code, e.g. 'A Coruña', 'Mérida, Badajoz', '08'.

Output parameters:

- `checks` (array)
- `confidence` (string): Lowest confidence across inputs: high, medium or low. Never state a conclusion more strongly than this.
- `data` (array)
- `sources` (array)

### `demographics` (~245 tokens)

Population and households

Population, sex, five-year age bands, 5-year trend, and household profile for a place in Spain.

Municipality, province and CCAA: census population by age band (latest 1 January),
cross-checked against the official Padrón figure. District and tract: census age bands
and sex from INE's file by census tract. Municipality, district and tract:
household size, single-person households, mean age, share under 18 and 65+ from INE's
income atlas. Use sub_areas to compare a city's districts or tracts, e.g. to find
where young families or older residents concentrate.

Input parameters:

- `place` (string, required): 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…
- `sub_areas` (string): For a municipality, also list its 'district's or census 'tract's. Default 'none'.

Output parameters:

- `checks` (array)
- `confidence` (string): Lowest confidence across inputs: high, medium or low. Never state a conclusion more strongly than this.
- `data`
- `sources` (array)

### `income` (~249 tokens)

Household income

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 parameters:

- `place` (string, required): 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…
- `rank_by` (string): Metric used to rank sub-areas.
- `sub_areas` (string): For a municipality, rank its 'district's or census 'tract's. Default 'none'.
- `years` (integer): Years of history for the trend (max 9).

Output parameters:

- `checks` (array)
- `confidence` (string): Lowest confidence across inputs: high, medium or low. Never state a conclusion more strongly than this.
- `data`
- `sources` (array)

### `businesses` (~519 tokens)

Businesses and competitors

Count businesses of a kind in a place in Spain, per 10,000 residents and per km², from OpenStreetMap.

Use it to size competition and supply: how many gyms, cafés or dentists an area has,
how that compares with the province, region and Spain, which brands dominate, and
which districts or tracts are over- or under-served (rank sub-areas by
per_10k_residents). Counts are lower bounds because OpenStreetMap is mapped by
volunteers; where INE's company directory covers the same activity, the result says
how complete the map looks in that region. Returns counts and brands only, never
lists of individual premises.

Input parameters:

- `category`: What to count. A category: restaurant, fast_food, cafe, bar, ice_cream, nightclub, supermarket, convenience, bakery, butcher, greengrocer, drinks_tobacco, clothes, pharmacy, optician, beauty_shop, je…
- `place` (string, required): 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…
- `rank_by` (string): How to rank sub-areas: 'count', 'per_10k_residents' or 'per_km2'.
- `sub_areas` (string): For a municipality, also count by 'district' or census 'tract'. Default 'none'.

Output parameters:

- `checks` (array)
- `confidence` (string): Lowest confidence across inputs: high, medium or low. Never state a conclusion more strongly than this.
- `data`
- `sources` (array)

### `market_size` (~338 tokens)

Market size in euros

Size the yearly market for a business category in a place in Spain, in euros, with a range.

Market = households × INE household spending on the category × an income adjustment.
Supply = competing businesses, calibrated against INE's company directory. Returns market
per business and an opportunity score: market per business against the region (1.0 = same as
the region), not a forecast of openings. Every assumption is listed. Assumptions can be overridden to test scenarios. Use for "how big
is the market for X in Y" and "is Y under-served for X".

Input parameters:

- `capture_share`: Share of the market one business could win (0-1), to estimate obtainable revenue.
- `category` (string, required): Business category: restaurant, cafe, bar, fast_food, bakery, butcher, greengrocer, supermarket, pharmacy, optician, dentist, physiotherapy, hairdresser, beauty_salon, veterinary, gym, childcare, priv…
- `competitors`: Override the estimated number of competing businesses.
- `place` (string, required): 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…
- `spend_per_household`: Override INE's yearly spend per household on the category, in euros.

Output parameters:

- `checks` (array)
- `confidence` (string): Lowest confidence across inputs: high, medium or low. Never state a conclusion more strongly than this.
- `data`
- `sources` (array)

### `compare_areas` (~244 tokens)

Compare areas for a business

Rank areas by market per competing business for a category (the opportunity score).

Each area gets a yearly market in euros, estimated competing businesses and an opportunity
score against its region, all with ranges. Areas are ranked by the cautious (low) end of
the score; areas too small for the category are left out and counted. Use for "where in
Valladolid should I open a gym" or "which towns in Málaga province lack pharmacies".

Input parameters:

- `category` (string, required): Business category: restaurant, cafe, bar, fast_food, bakery, butcher, greengrocer, supermarket, pharmacy, optician, dentist, physiotherapy, hairdresser, beauty_salon, veterinary, gym, childcare, priv…
- `level` (string): 'district' or 'tract' within a municipality; 'municipality' within a province or region.
- `limit` (integer): How many areas to return, best first.
- `within` (string, required): A municipality (compares its districts or tracts) or a province or region (compares its municipalities).

Output parameters:

- `checks` (array)
- `confidence` (string): Lowest confidence across inputs: high, medium or low. Never state a conclusion more strongly than this.
- `data`
- `sources` (array)

### `catchment` (~212 tokens)

Catchment around an address

Profile the area within a radius (or a walking time) of an address: residents, households, income, age, and
the businesses mapped there. With a category, also the yearly market in euros, competing
businesses and an opportunity score against the region. Use for "who lives within 800 m of
this shop" or "is there room for a bakery near Calle X". Addresses are checked against the
municipality they name; ambiguous ones are refused with suggestions.

Input parameters:

- `category`: Optional business category, to add market size and opportunity score.
- `near` (string, required): Address as 'street number, municipality' (e.g. 'Calle Sierpes 40, Sevilla'), or coordinates as 'lat, lon'. Floor and door are ignored and never stored.
- `radius_m` (integer): Radius in metres (e.g. 500, 800, 1500).
- `walk_minutes`: Use the area reachable on foot in this many minutes instead of a circle.

Output parameters:

- `checks` (array)
- `confidence` (string): Lowest confidence across inputs: high, medium or low. Never state a conclusion more strongly than this.
- `data`
- `sources` (array)

### `price_band` (~265 tokens)

Price range for a place

Suggest a price range for a place from local purchasing power and inflation.

Public data has no competitor prices, so this adjusts a price you know (from elsewhere or
an earlier date) to this place today: CPI for the category's group since that month, then
local median income per consumption unit against the reference place. Returns a range
from no local adjustment to full adjustment, labelled as an estimate.

Input parameters:

- `category`: Market category, to uprate with its own CPI group (e.g. 'gym', 'restaurant').
- `place` (string, required): 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…
- `price_month`: Month the reference price applied, YYYY-MM, to uprate it to today.
- `reference_place` (string): Where the reference price applies: 'ES' (Spain, default) or a place.
- `reference_price` (number, required): Price elsewhere, in euros, e.g. 39.9 for a monthly gym fee.

Output parameters:

- `checks` (array)
- `confidence` (string): Lowest confidence across inputs: high, medium or low. Never state a conclusion more strongly than this.
- `data`
- `sources` (array)

### `chart` (~217 tokens)

Chart

Draw a chart (PNG) of a tool result: an opportunity ranking with ranges, income by district,
an age pyramid or a population trend. Returns the image, the same text and sources as the
underlying tool, and a source line on the image. If drawing fails the text still comes back.

Input parameters:

- `category`: Business category, for kind 'opportunity'.
- `kind` (string, required): 'opportunity' (needs category; ranks areas within the place), 'income' (by district or tract), 'age_pyramid' or 'population_trend'.
- `place` (string, required): 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…
- `sub_areas` (string): For 'income': districts or tracts.

Output parameters:

- `checks` (array)
- `confidence` (string): Lowest confidence across inputs: high, medium or low. Never state a conclusion more strongly than this.
- `data`
- `sources` (array)

### `rents` (~170 tokens)

Rents

How housing rents have changed in a place: INE's rent index (IPVA, 2015 = 100) with the
change over the last year, five years and since 2015, against province, region and Spain.

Covers municipalities over 10,000 residents, districts of provincial capitals, provinces and
regions (not the Basque Country or Navarra). Gives changes, not rents in euros.

Input parameters:

- `place` (string, required): 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…

Output parameters:

- `checks` (array)
- `confidence` (string): Lowest confidence across inputs: high, medium or low. Never state a conclusion more strongly than this.
- `data`
- `sources` (array)

### `crime` (~182 tokens)

Crime

Recorded crime in a place from the Interior ministry: offences by type (theft, burglary,
robbery, assault, drugs, cybercrime and more) for the latest full year, per 1,000 residents,
the change on the year before, the latest year-to-date figures, and province, region and
Spain for comparison.

Published for municipalities over 20,000 residents, provinces and regions; smaller places
get the province's figures, and the result says so.

Input parameters:

- `place` (string, required): 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…

Output parameters:

- `checks` (array)
- `confidence` (string): Lowest confidence across inputs: high, medium or low. Never state a conclusion more strongly than this.
- `data`
- `sources` (array)

### `find_datasets` (~135 tokens)

Find open datasets

Search Spain's national open-data catalogue (datos.gob.es) for datasets on a topic.

Returns each dataset's title, publisher, licence, file formats, update frequency and last
change, and an id to pass to read_dataset. Use when a question needs data this server does
not hold directly (parking, licences, local events, tourist offices, transport).

Input parameters:

- `limit` (integer): How many datasets to return.
- `place`: Optional place; datasets about it are preferred.
- `query` (string, required): Topic; Spanish works best, e.g. 'turismo', 'aparcamiento', 'licencias'.

Output parameters:

- `checks` (array)
- `confidence` (string): Lowest confidence across inputs: high, medium or low. Never state a conclusion more strongly than this.
- `data`
- `sources` (array)

### `read_dataset` (~112 tokens)

Read an open dataset

Read a datos.gob.es dataset: its columns and up to 20 sample rows, with its licence.

Reads CSV and JSON files listed in the catalogue (the first 5 MB). Columns that look like
personal data (names, ID numbers, emails, phones) are withheld. Values are shown as the
publisher published them.

Input parameters:

- `dataset_id` (string, required): An id from find_datasets.
- `file_index`: Which file of the dataset (from 0); default: the first CSV or JSON.

Output parameters:

- `checks` (array)
- `confidence` (string): Lowest confidence across inputs: high, medium or low. Never state a conclusion more strongly than this.
- `data`
- `sources` (array)

## Diagnostics

Captured diagnostic sections: Provenance, Install scripts, Dependencies. The full working is on the page: https://verifymcp.io/servers/digvijaysingh-ai-spain-open-data-mcp/spain-open-data-mcp#diagnostics

## Score history

- 2026-10-25: 81
- 2026-10-24: 81
- 2026-10-23: 81
- 2026-10-22: 81
- 2026-10-21: 81
- 2026-10-20: 81
- 2026-10-19: 81
- 2026-10-18: 81
- 2026-10-17: 66

## Common questions

### What is the Spain Open Data MCP server?

Spain Open Data is an MCP server listed in the public MCP registry as io.github.digvijaysingh-ai/spain-open-data-mcp. Market sizing, prices, rents, crime and locations in Spain from INE and other public data. This page covers its PyPI package (spain-open-data-mcp).

### Is the Spain Open Data MCP server safe to use?

Spain Open Data scores 81 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 25 October 2026. Its build provenance is signed and verified. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

### What tools does the Spain Open Data MCP server expose?

Spain Open Data exposes 13 tools: resolve_place, demographics, income, businesses, market_size, and 8 more. Their descriptions and schemas cost roughly 3,077 tokens of context every time the server is loaded.

### Is the Spain Open Data MCP server still maintained?

Spain Open Data is still listed as active in the MCP registry. We last reached this channel on 25 October 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

### What licence is the Spain Open Data MCP server under?

Spain Open Data declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.

## Links

- PyPI project: https://pypi.org/project/spain-open-data-mcp/
- Socket report: https://socket.dev/pypi/package/spain-open-data-mcp
- Repository: https://github.com/digvijaysingh-ai/spain-open-data-mcp
- Website: https://digvijaysingh-ai.github.io/spain-open-data-mcp/
- Changelog RSS feed: https://verifymcp.io/servers/digvijaysingh-ai-spain-open-data-mcp/spain-open-data-mcp.xml
- Changelog JSON feed: https://verifymcp.io/servers/digvijaysingh-ai-spain-open-data-mcp/spain-open-data-mcp.json
- HTML version of this page: https://verifymcp.io/servers/digvijaysingh-ai-spain-open-data-mcp/spain-open-data-mcp