Stats Compass MCP Server
stats-compass-mcp
PyPI
v0.3.28
Published by an unidentified publisher — no publish provenance and no public repository, so the publisher could not be verified and the source cannot be independently located.
MCP server exposing stats-compass-core tools to LLMs like ChatGPT, Claude, and Gemini
The grade answers one question — how safe is this server for you to adopt — so it is computed in two auditable stages. Nothing below is an opinion or an LLM's guess; every line is a real term the deterministic engine applied, and the same input always yields the same number.
1. Threat score — 100 − 0 = 100. What the published surface and source actually contain:
The deterministic scan raised no scored threat in the surface it inspected — the threat score stayed at 100. Capability observations and advisory notes are recorded but never lower it.
2. Client adoption risk — 100 − 5 = 95. Three small, subtract-only factors that reflect your risk in adopting it — a clean scan proves less on a powerful, unverified or barely-inspectable package, so the grade says so plainly:
| Points | Adoption-risk factor |
|---|---|
| −3 | capability blast radius (moderate) — client exposure if the model is manipulated |
| −2 | publisher verification (unlinked) — no provenance/repo link, but the shipped source was fully read |
Capability observations and info notes are shown under Findings but never scored.
Open any row's finding below for the file, line and evidence behind a deduction.
Findings 0
Tools 33
Each tool and what it can reach — statically extracted from the published source.
describe_data_toolsingests untrusted inputreads sensitive datalist_filesreads sensitive datasave_modelingests untrusted inputdelete_sessionno sensitive capabilitydescribe_cleaning_toolsno sensitive capabilitydescribe_eda_toolsno sensitive capabilitydescribe_ml_toolsno sensitive capabilitydescribe_plot_toolsno sensitive capabilitydescribe_transform_toolsno sensitive capabilityexecute_cleaning_toolno sensitive capability
Show 23 more tools ↓
execute_data_toolno sensitive capabilityexecute_eda_toolno sensitive capabilityexecute_ml_toolno sensitive capabilityexecute_plot_toolno sensitive capabilityexecute_transform_toolno sensitive capabilityget_sampleno sensitive capabilityget_schemano sensitive capabilityget_upload_urlno sensitive capabilityget_usage_guideno sensitive capabilitylist_dataframesno sensitive capabilityload_csvno sensitive capabilityload_datasetno sensitive capabilityload_excelno sensitive capabilitypingno sensitive capabilityregister_uploaded_fileno sensitive capabilityrun_classification_workflowno sensitive capabilityrun_eda_report_workflowno sensitive capabilityrun_preprocessing_workflowno sensitive capabilityrun_regression_workflowno sensitive capabilityrun_timeseries_workflowno sensitive capabilitysave_csvno sensitive capabilityserver_statsno sensitive capabilitysession_infono sensitive capability
What this scan could not see
- Tools were statically extracted from the published source (33 recovered), not enumerated from a running server. Tool-poisoning, Unicode-smuggling, capability and toxic-flow analysis ran on this inferred surface, but a mis-parsed registration could be missed or mis-attributed, so tool-derived findings are capped below “confirmed”. To grade the real runtime surface, scan the running server: --command "npx -y <package>".
Versions 3
Scan history per published version. The engine is deterministic — the same version always yields the same score, so a changed score means the package itself changed.
| Version | Score | Findings | Engine | Scanned |
|---|---|---|---|---|
v0.3.28 latest |
A 95/100 | 0 | 1.13.0 | 2026-08-27 |
v0.3.23 |
A 95/100 | 0 | 1.13.0 | 2026-08-25 |
v0.3.22 |
A 95/100 | 0 | 1.12.1 | 2026-07-27 |
Embed this score
Show this server's live Trust Score in your README, docs or website. The badge is served straight from the registry and updates automatically after every rescan — no API key needed. It links back to this page, so anyone who sees the grade can also read the findings behind it instead of taking a number on faith.
Verify this score yourself
The score above is reproducible: the same package version always yields the same result. Run it locally or over the free API — no account, no LLM, fully deterministic.
npx mcptrustchecker scan stats-compass-mcp --online --registry pypiMore in Developer Tools
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