MCP Observatory
github re-analysis due

mizcausevic-dev/mcp-ai-tutor

github

MCP server for AI Tutor Card disclosures. Six tools for procurement review, curriculum matching, and FERPA / COPPA compliance auditing of AI tutors. EdTech-flavored extension of the Kinetic Gain Protocol Suite.

maintainer
mizcausevic-dev
license
AGPL-3.0
first seen
2026-06-11
last seen
2026-06-11
releases · 30d
0
short id
risk 6/100 · heuristic grade
A minimal
  • capability exposureinferred+6

inferred

The A–E grade is our heuristic synthesis — a "review this" prompt, not a verdict. Each factor is tagged by what backs it: attested (a verifiable record), reported (a third party's claim), or inferred (our own heuristic, e.g. permissions). See methodology.

graded 13m ago · see ecosystem CVEs →

risk trajectory 2 movements
  • A · 10 → A · 6
  • A · 12 → A · 10
capability exposure grade factor +6
Inferred surface — each links to servers holding it:
vulnerabilities 0 CVEs

No known CVEs for this server.

tool safety all quiet

No tool-safety findings — heuristic detectors run on the compute-risk cadence; a finding appears when a tool trips a rule.

embed badge readme-ready
live risk-grade badge preview [![MCP Observatory risk grade](https://mcpobservatory.com/servers/github:mizcausevic-dev/mcp-ai-tutor/badge.svg)](https://mcpobservatory.com/servers/github:mizcausevic-dev/mcp-ai-tutor/security)

Heuristic, inferred signals — false positives (legitimately powerful tools, forks, language ports) are expected. Treat each as "review this", not a verdict. See the ecosystem-wide picture on the security hub, or the fleet security of mizcausevic-dev.