StatsMapped Public Data
PYPI · STATSMAPPED-MCP · 2 COMPONENTS
Public statistics for Ireland and the UK: housing, crime, health, economy, welfare, with caveats.
Available components
Last scanned (18 hours ago)
Scores higher than 88% of PyPI servers
Category Data and Analytics
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. How we score → Why this is hard to score →
Supply Chain Security100
- No malware found by supply-chain analysis.Pass
- No known CVEs affecting this package version or its production dependencies.Pass
- Runs hatchling.build at install time, a recognised build step with no custom scripting around it. View diagnostics → Pass
- 1 of 31 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency97
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Cryptographically verified build provenance (signed, bound to ActiveGuy/statsmapped-mcp). View diagnostics → Pass
- Clear OSI-approved license (MIT).Pass
- Actively maintained (last published 5 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability56
- AI-judged instruction clarity (excellent).Pass
- Context-footprint check failed: tool/resource definitions use about 1887 tokens (~471/item across 4 items; 4 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management73
- Stability observed for 22 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage71
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 0% of tool parameters carry a description.Fail
- Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 4 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 4 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a current MCP spec version (2026-07-28).Pass
Checks we ran (16)
- Malware scan
- Known CVEs
- Install scripts
- Dependency health
- Source repository
- Provenance
- License
- Maintenance
- Security disclosure
- Schema quality
- Stability
- Tool coverage
- Injection markers
- Destructive annotations
- Judged manipulation
- MCP protocol
Does not apply to this package (2)
- Endpoint SecurityScored on hosted endpoints only. A package has no live endpoint of its own for us to probe.
- Transport & ReachabilityScored on hosted endpoints only. A package has no live endpoint of its own for us to probe.
The score does not measure everything. What the score does not measure →
Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 5 Nov 26 +15
- Malware scan: unverified → pass ▲ security
- 4 Nov 26 −15
- Malware scan: pass → unverified ▼ security
- 3 Nov 26 +16
- Malware scan: unverified → pass ▲ security
- 2 Nov 26 −15
- Malware scan: pass → unverified ▼ security
- 1 Nov 26 +16
- Malware scan: unverified → pass ▲ security
- 31 Oct 26 −15
- Malware scan: pass → unverified ▼ security
- 30 Oct 26 +16
- Malware scan: unverified → pass ▲ security
- 28 Oct 26 −14
- Malware scan: pass → unverified ▼ security
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 5 Nov 2026 · Analysed pypi/statsmapped-mcp@0.3.2
Provenance Verified
A signed build attestation was found and verified, binding this exact artifact to the source repository it claims to come from.
| Result | Verified |
|---|---|
| Ecosystem | pypi |
| Reason | Verified |
| Discovered via | Registry attestation endpoint |
| Source repo | ActiveGuy/statsmapped-mcp |
| Certificate issuer | https://token.actions.githubusercontent.com |
| Certificate SAN | https://github.com/ActiveGuy/statsmapped-mcp/.github/workflows/publish.yml@refs/tags/v0.3.2 |
| Rekor log index | 3179607884 |
| Predicate type | PyPI publish attestation https://docs.pypi.org/attestations/publish/v1 |
| Subject digest | sha256:20f590d1675b782da933c3d1575d31c6254ba719e37a477e2406b66cae1a344d |
Background: How many MCP packages publish verified provenance →
Install scripts 1 script
| Hook | Tier | Command |
|---|---|---|
| build_backend | Known build tool | hatchling.build |
Background: Why install scripts are a supply-chain risk →
Dependencies 31 packages
| Packages resolved | 31 |
|---|---|
| No linked repository | 1 |
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
compare ~1,080
Four modes, depending on which arguments are given -- consolidates what were four separate tools (rank_areas, list_comparisons, get_comparison, check_comparability) behind one, since they are all really "how does this stat compare" at different scopes. Exactly one mode's arguments should be given; mixing arguments from different modes (e.g. both `stat_key` and `pair_key`, or only one of `stat_key_a`/`stat_key_b`) raises an error rather than silently guessing which mode was meant. 1. `stat_key` alone (no `pair_key`, no `stat_key_a`/`stat_key_b`): ranks every area at one geography level by its latest figure for that stat, for one country -- e.g. "which counties have the highest median sale price" (country="ireland"). `stat_key` comes from `query_data`'s dataset-listing mode, for the SAME country. `level` omitted uses this ranking's own default level; pass one of that dataset's own `compatible_levels` for a different one -- a level this ranking doesn't have registered returns an empty list rather than an error. Where the underlying stat has no honest per-area denominator (crime, homelessness, live_register and similar -- StatsMapped's own RANKING_NO_DENOMINATOR_STATS), each row's `rate_per_1000` is the real figure to rank/compare by, not `latest_value`, which is a raw count dominated by area population size. Always carry forward every entry in `caveats` when using a row in an answer. 2. `pair_key` alone: full detail for one registered comparison pair -- each axis's label, unit and publisher, the correlation stats (r, rho, and a leave-one-out sensitivity range naming the single most influential area), and caveats. `pair_key` comes from mode 4's own response, for the SAME country. 3. Both `stat_key_a` and `stat_key_b` given: does StatsMapped have a registered, hand-vetted comparison between these two stats? Registry- backed only -- never computes a fresh correlation for an arbitrary pair. Both stat_keys come f…
| Name | Type | Req | Description |
|---|---|---|---|
| country | string | – | – |
| level | – | – | – |
| pair_key | – | – | – |
| stat_key | – | – | – |
| stat_key_a | – | – | – |
| stat_key_b | – | – | – |
| Name | Type | Req | Description |
|---|---|---|---|
| result | – | yes | – |
No examples provided.
explain_metric ~124
Definition, methodology and standing caveats for ONE stat ('ireland' or 'united-kingdom') -- never a current figure. Call this when the question is about what a metric MEANS or how it's measured ("how is the claimant count defined", "is this a mean or a median"), not about a specific area's value -- `query_data`/`compare` already answer that. `stat_key` comes from `query_data(country=...)` for the SAME country.
| Name | Type | Req | Description |
|---|---|---|---|
| country | string | – | – |
| stat_key | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
list_areas ~161
List every geography at one boundary level, for one country ('ireland' or 'united-kingdom'). `level` defaults to "county" (Ireland's 26 counties); the UK's own primary level is "lad" (local authority districts), not "county". Other levels exist per country (e.g. Ireland's "local_authority", "garda_division") -- see a dataset's own `compatible_levels` from `query_data` for which levels a given stat is actually published at. Returns each area's `id` (used by `query_data`'s area-scoped modes, always paired with the SAME `country`) and `name`.
| Name | Type | Req | Description |
|---|---|---|---|
| country | string | – | – |
| level | string | – | – |
| Name | Type | Req | Description |
|---|---|---|---|
| result | array | yes | – |
No examples provided.
query_data ~522
Three modes, depending on which of `area_id`/`dataset` are given -- consolidates what were three separate tools (list_datasets, list_area_datasets, get_dataset_for_area) behind one, since they are all really "how do I get data" at different levels of specificity: 1. Neither `area_id` nor `dataset`: lists every dataset (stat) StatsMapped tracks for one country ('ireland' or 'united-kingdom'), with its key, human label, and which geography levels it can be shown at. Ireland and the UK track genuinely different datasets -- call this first for the right country before assuming a stat_key exists there, to find the right `stat_key` for `compare`'s ranking mode. 2. `area_id` given, `dataset` omitted: lists every dataset available for that one area (e.g. "county:kerry" for Ireland, "uk:lad:e09000033" for the UK), with its latest figure, year-on-year change, and caveat labels only (not full caveat text -- use mode 3 for the full detail on any one dataset that matters). `area_id` comes from `list_areas`; `country` must match whichever country that call used, or this simply 404s ("unknown geography"). 3. Both `area_id` and `dataset` given: full detail for one dataset in one area -- the latest figure, a written summary, full caveat text, and (if `history_months` is set) recent history. `dataset` is a `series_key` from mode 2's own response. `history_months` means actual months of history (0 = everything) -- e.g. 24 returns 2 years of an annual series, not 24 years. `country` must match `area_id`'s own country. `dataset` and `history_months` are only meaningful together with `area_id` (and, for `history_months`, `dataset` too, since it only applies to mode 3); giving either without its real precondition raises rather than silently dropping the argument and dispatching to the wrong mode.
| Name | Type | Req | Description |
|---|---|---|---|
| area_id | – | – | – |
| country | string | – | – |
| dataset | – | – | – |
| history_months | integer | – | – |
| Name | Type | Req | Description |
|---|---|---|---|
| result | – | yes | – |
No examples provided.
How do I install the StatsMapped Public Data MCP server?
StatsMapped Public Data runs locally as a PyPI package, launched with uvx statsmapped-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · statsmapped-mcp
claude mcp add com-statsmapped-public-data -- uvx statsmapped-mcp
What is the StatsMapped Public Data MCP server?
StatsMapped Public Data is an MCP server listed in the public MCP registry as com.statsmapped/public-data. Public statistics for Ireland and the UK: housing, crime, health, economy, welfare, with caveats. This page covers its PyPI package (statsmapped-mcp).
Is the StatsMapped Public Data MCP server safe to use?
StatsMapped Public Data scores 85 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 5 November 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 StatsMapped Public Data MCP server expose?
StatsMapped Public Data exposes 4 tools: query_data, list_areas, compare, explain_metric. Their descriptions and schemas cost roughly 1,887 tokens of context every time the server is loaded.
Is the StatsMapped Public Data MCP server still maintained?
StatsMapped Public Data is still listed as active in the MCP registry. We last reached this channel on 5 November 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 StatsMapped Public Data MCP server under?
StatsMapped Public 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.
What did VerifyMCP test on the StatsMapped Public Data MCP server?
VerifyMCP ran 16 checks on StatsMapped Public Data, covering Malware scan, Known CVEs, Install scripts, Dependency health and 12 more. Endpoint Security and Transport & Reachability do not apply to a PyPI package, so they were not tested. The score does not measure everything, and the scoring documentation lists what it leaves out.