evernote-mcp
PyPI
v0.4.1
Published by king — no publish provenance, so origin is unverified, but the source is public: the repository link below is self-declared yet readable, so you can inspect the code before adopting it.
Model Context Protocol (MCP) server for Evernote operations
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 − 1 = 99. 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 |
|---|---|
| −1 | publisher verification (public source) — no provenance, but the source is public and inspectable |
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.
Each tool and what it can reach — statically extracted from the published source.
clear_reminderno sensitive capabilitycomplete_reminderno sensitive capabilitycopy_noteno sensitive capabilitycreate_noteno sensitive capabilitycreate_notebookno sensitive capabilitycreate_searchno sensitive capabilitycreate_tagno sensitive capabilitydelete_noteno sensitive capabilitydelete_notebookno sensitive capabilityexpunge_noteno sensitive capabilityexpunge_searchno sensitive capabilityexpunge_tagno sensitive capabilityfind_note_countsno sensitive capabilityfind_relatedno sensitive capabilityget_default_notebookno sensitive capabilityget_noteno sensitive capabilityget_note_contentno sensitive capabilityget_note_search_textno sensitive capabilityget_note_tag_namesno sensitive capabilityget_note_versionno sensitive capabilityget_notebookno sensitive capabilityget_reminderno sensitive capabilityget_resourceno sensitive capabilityget_resource_alternate_datano sensitive capabilityget_resource_application_datano sensitive capabilityget_resource_application_data_entryno sensitive capabilityget_resource_attributesno sensitive capabilityget_resource_by_hashno sensitive capabilityget_resource_datano sensitive capabilityget_resource_recognitionno sensitive capabilityget_resource_search_textno sensitive capabilityget_searchno sensitive capabilityget_sync_stateno sensitive capabilityget_tagno sensitive capabilitylist_note_versionsno sensitive capabilitylist_notebooksno sensitive capabilitylist_notesno sensitive capabilitylist_remindersno sensitive capabilitylist_searchesno sensitive capabilitylist_tagsno sensitive capabilitylist_tags_by_notebookno sensitive capabilitymove_noteno sensitive capabilitysearch_notesno sensitive capabilityset_reminderno sensitive capabilityset_resource_application_data_entryno sensitive capabilityunset_resource_application_data_entryno sensitive capabilityuntag_allno sensitive capabilityupdate_noteno sensitive capabilityupdate_notebookno sensitive capabilityupdate_resourceno sensitive capabilityupdate_searchno sensitive capabilityupdate_tagno sensitive capabilityScan 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 |
|---|---|---|---|---|
v0.4.1 latest |
A 99/100 | 0 | 1.13.0 | 2026-08-25 |
v0.3.5 |
A 99/100 | 0 | 1.12.1 | 2026-07-27 |
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.
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 evernote-mcp --online --registry pypi
Independent packages implementing the same tool, scanned with the same engine. Compare all 3 side by side →
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