MCP Observatory
8m ago Tracked 21,444 Last 8m ago 24h 1,334
github analyzed 2ec033d

shadowresearch/auto-geo

github

GEO optimized content publishing engine for AI visibility. MIT, by Shadow.

maintainer
shadowresearch
license
MIT
first seen
2026-06-04
last seen
2026-06-10
releases · 30d
18
short id
risk 32/100 · heuristic grade
B low
  • capability exposureinferred+35
  • trust mitigatorsmixed−3

inferredmixed

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 5m ago · see ecosystem CVEs →

risk trajectory 2 movements
  • B · 25 → B · 32
  • A · 0 → B · 25
capability exposure grade factor +35
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.

skills & danger signals github-tarball
prompt-surface shipped agent-instruction files + hidden-content / dangerous-code findings — quoted from the analyzed source

analyzed commit 2ec033d · analyzer v20 · 8h ago

skills & prompt files 1

embed badge readme-ready
live risk-grade badge preview [![MCP Observatory risk grade](https://mcpobservatory.com/servers/github:shadowresearch/auto-geo/badge.svg)](https://mcpobservatory.com/servers/github:shadowresearch/auto-geo/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 shadowresearch.