Universal Memory (YanAmorelli) MCP Server
universal-memory
PyPI
v0.6.1
Published by yanamorelli — 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.
Vendor-agnostic cognitive persistence layer for AI agents.
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 − 7 = 93. 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 |
|---|---|
| −6 | capability blast radius (high) — client exposure if the model is manipulated |
| −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.
Findings 3
high Shell/command execution in server code (application/layout/inspect_project_layout.py)MTC-SRC-002
In the server's implementation (`application/layout/inspect_project_layout.py:220`): Spawning a shell/process is command-execution capability; with unsanitized tool input it is command injection / RCE. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: try: return subprocess.run( # noqa: S603 [git, "-C", project_root.as_posix(), *args],
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server application/layout/inspect_project_layout.py
high Shell/command execution in server code (application/skills/native_skill_sync.py)MTC-SRC-002
In the server's implementation (`application/skills/native_skill_sync.py:418`): Spawning a shell/process is command-execution capability; with unsanitized tool input it is command injection / RCE. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: ) -> bool: result = subprocess.run( # noqa: S603 ["git", "check-ignore", "-q", "--", relative_path], # noq
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server application/skills/native_skill_sync.py
high Shell/command execution in server code (application/skills/official_skill_release.py)MTC-SRC-002
In the server's implementation (`application/skills/official_skill_release.py:168`): Spawning a shell/process is command-execution capability; with unsanitized tool input it is command injection / RCE. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: tion.") completed = subprocess.run( # noqa: S603 [git_path, *arguments], cwd=project_root,
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server application/skills/official_skill_release.py
Tools 38
Each tool and what it can reach — statically extracted from the published source.
activate_skillno sensitive capabilityadopt_skillno sensitive capabilitybootstrapno sensitive capabilitycleanup_skillno sensitive capabilitycontextno sensitive capabilitycreate_skillno sensitive capabilitycreate_skill_draftno sensitive capabilitydeactivate_skillno sensitive capabilitydoctorno sensitive capabilitygenerate_skillno sensitive capability
Show 28 more tools ↓
get_skill_detailno sensitive capabilityhost_checkno sensitive capabilityhost_setupno sensitive capabilityimport_skillno sensitive capabilityinitialize_projectno sensitive capabilityinspect_project_layoutno sensitive capabilitylist_audit_eventsno sensitive capabilitylist_factsno sensitive capabilitylist_skillsno sensitive capabilitylist_snapshotsno sensitive capabilitymigrate_project_layoutno sensitive capabilitypromote_skill_recommendationno sensitive capabilitypropose_skillno sensitive capabilitypublish_skillno sensitive capabilitypurge_factno sensitive capabilityrecommend_skillsno sensitive capabilityremember_factno sensitive capabilityrename_skillno sensitive capabilityrepair_skillsno sensitive capabilityrollback_scopeno sensitive capabilityshare_skillno sensitive capabilitystatusno sensitive capabilitysync_instructionsno sensitive capabilitysync_skillsno sensitive capabilitytrack_latent_skillno sensitive capabilityupdate_canonical_skillno sensitive capabilityupdate_skillno sensitive capabilityvalidate_skillno sensitive capability
What this scan could not see
- Tools were statically extracted from the published source (38 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 4
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 |
|---|---|---|---|---|
v0.6.1 latest |
A 93/100 | 3 | 1.13.0 | 2026-08-27 |
v0.5.1 |
A 93/100 | 3 | 1.13.0 | 2026-08-25 |
v0.5.0 |
A 93/100 | 3 | 1.12.1 | 2026-08-03 |
v0.4.0 |
A 93/100 | 2 | 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 universal-memory --online --registry pypiOther implementations of Universal Memory 1
Independent packages implementing the same tool, scanned with the same engine. Compare all 2 side by side →
More in AI, Memory & Reasoning
FDA device & vehicle recall risk for AI agents: recall history, MAUDE trend, risk score.
Open-source MCP server exposing Agent402.Tools' catalog — 500+ strong: 400+ self-hostable tools + 100 multi-tool skill packs (security-audit, trend-analysis, structured-scrape, decode-blob, forecasting-bake-off) for AI agents — browser, web search & answe
Zero-dependency MCP server that gives AI agents a self-updating project memory in AGENTS.md. Returns merge instructions instead of mutating state, so every change is a reviewable diff.
MCP Apps UI resources and server helpers for n8n
MCP server providing comprehensive access to BookStack knowledge management system
MCP server for tracking achievements with STAR methodology