github analyzed 7a461b2

jenkinsm13/metashape-mcp

github

AI-powered photogrammetry automation — MCP server for Agisoft Metashape Professional 2.3+. Control the full pipeline (alignment, dense cloud, mesh, texture, DEM, orthomosaic, export) using natural language through Claude or any MCP-compatible AI assistant.

maintainer
jenkinsm13
license
MIT
first seen
2026-06-01
last seen
2026-06-04
releases · 30d
0
short id
risk46/100 · heuristic grade
C elevated
  • capability exposureinferred+22
  • recent driftinferred+12
  • tool safetyinferred+12

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 10m ago · see ecosystem CVEs →

risk trajectory1 movements
  • A · 0C · 46
capability exposuregrade factor +22
Inferred surface — each links to servers holding it:
vulnerabilities0 CVEs

no known CVEs for this server.

tool safety1 findings · grade factor +12
  1. highdangerous code

    dynamic exec: __import__()

skills & danger signalsgithub-tarball
other grade factorsevidence elsewhere
embed badgereadme-ready
live risk-grade badge preview [![MCP Observatory risk grade](https://mcpobservatory.com/servers/github:jenkinsm13/metashape-mcp/badge.svg)](https://mcpobservatory.com/servers/github:jenkinsm13/metashape-mcp/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 jenkinsm13.