Onetrust Api MCP Server
onetrust-api
PyPI
v0.2.1
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.
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 − 2 = 98. 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 |
|---|---|
| −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 36
Each tool and what it can reach — statically extracted from the published source.
onetrust_access_managementno sensitive capabilityonetrust_ai_governanceno sensitive capabilityonetrust_api_requestno sensitive capabilityonetrust_assessmentsno sensitive capabilityonetrust_audit_managementno sensitive capabilityonetrust_bulk_exportno sensitive capabilityonetrust_cmpno sensitive capabilityonetrust_compliance_automationno sensitive capabilityonetrust_consent_interfacesno sensitive capabilityonetrust_consent_receiptsno sensitive capability
Show 26 more tools ↓
onetrust_cookie_consentno sensitive capabilityonetrust_cookie_consent_legacyno sensitive capabilityonetrust_cookie_domain_datano sensitive capabilityonetrust_cross_device_consentno sensitive capabilityonetrust_data_catalogno sensitive capabilityonetrust_data_discoveryno sensitive capabilityonetrust_data_discovery_workerno sensitive capabilityonetrust_data_mappingno sensitive capabilityonetrust_data_mapping_legacyno sensitive capabilityonetrust_documentsno sensitive capabilityonetrust_dsarno sensitive capabilityonetrust_esgno sensitive capabilityonetrust_incidentsno sensitive capabilityonetrust_integrationsno sensitive capabilityonetrust_inventoryno sensitive capabilityonetrust_issues_managementno sensitive capabilityonetrust_it_risk_managementno sensitive capabilityonetrust_mobile_app_consentno sensitive capabilityonetrust_object_managerno sensitive capabilityonetrust_policy_managementno sensitive capabilityonetrust_privacy_noticesno sensitive capabilityonetrust_task_managementno sensitive capabilityonetrust_tprmno sensitive capabilityonetrust_trainingno sensitive capabilityonetrust_universal_consentno sensitive capabilityonetrust_user_provisioningno sensitive capability
What this scan could not see
- Tools were statically extracted from the published source (36 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 1
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 |
|---|---|---|---|---|
v0.2.1 latest |
A 98/100 | 0 | 1.8.0 | 2026-07-23 |
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.
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