Is Idescat MCP Server safe?
Yes, with the usual care.
Passed every safety check we run. Maintained, authenticated, reachable, clean scan.
No critical or high findings in the latest scan.
Public scan report
scanner v0.1.9 · 2026-09-20 · same rubric, same numbers if you re-run it
1 low
- –Code scanremote-only server, no package to scann/a
- Live reliabilityremote reachable in 1962ms20/20
- Tool poisoning7 tool descriptions checked13/15
- Auth qualityopen endpoint, read-only tools10/15
- Maintenancelast push 11 days ago15/15
- Maintainer identityregistry namespace matches repository owner; GitHub account older than a year; website matches verified namespace10/10
Findings (1)
- lowUnusually long tool description (over 2,000 characters)
poison.long-descriptiontool get_table_data: …Retrieves the data (values) of an Idescat table in JSON-stat format for a territorial division. You can retrieve the ENTIRE table (without filters) or only a SUBSET by passing the OPTIONAL parameters 'filters' (specific categories per dimension) and/or 'last' (number of last time periods); filtering returns smaller responses and allows querying tables that as a whole would exceed the limit. The filters use the dimension identifiers and category codes (category.index) returned by get_table_metadata (with the same 'geo'). IMPORTANT: the 20,000 cell limit is checked AFTER applying the filters; if it exceeds it, it returns a 'Dataset too large' error and you must add more filters (filters, last). You can call get_table_metadata beforehand to know the dimensions, periods, and category codes. The result contains: 'id' (dimension names in order), 'size' (number of categories per dimension), 'value' (flat array of values), 'dimension' (details per dimension: codes in category.index, labels in category.label, units in category.unit), 'role' (which dimensions are time, geo, or metric), 'status' (marks special values). HOW TO READ 'value' (row-major order): the array is FLAT; the LAST dimension of 'id' varies fastest and the first slowest. To get the value of a combination of categories (one per dimension) follow these 4 steps: (1) for each dimension, look for the POSITION (0-based) of the chosen category in dimension.{nom}.category.index — this 'index' can be a code→position object or a list of codes (the position is the index within the list); ALWAYS use this index, DO NOT assume alphabetical order or by label; (2) the stride of each dimension = product of the 'size' of the SUBSEQUENT dimensions (the last dimension has stride 1); (3) offset = sum of (position × stride) of all dimensions; (4) the searched value is value[offset]. Use the order of the 'id' array in all steps (NOT the order of keys in 'dimension'). EXAMPLE: id=['territory','sex'], size=[3,2], territory.index={BCN:0,GIR:1,LLE:2}, sex.index={M:0,F:1} → strides=[2,1]; for Girona+Woman: offset = 1×2 + 1×1 = 3, i.e., value[3]. Canonical ordering sample: https://json-stat.org/samples/order.json. WARNINGS: 1) null values (data not available) OCCUPY their position within the order: they DO NOT shift the index. 2) 'Base 2024', 'Base 2024=100' or '2024 Statistical Revision' in the title DO NOT indicate estimates; they are only the year of methodological reference and the data are real and definitive unless 'status' indicates otherwise.…
Overall 91/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON