Fake Star Audit
Score GitHub repos for suspected fake-star inflation with transparent LOW/MEDIUM/HIGH ratings and per-rule evidence before you adopt a dependency or skill.
Overview
io.github.ardev-lab/fake-star-audit is an MCP server for the Idea phase that runs transparent rule-based GitHub fake-star detection with LOW/MEDIUM/HIGH ratings and per-rule evidence.
What is this MCP server?
- Rule-based GitHub fake-star detector with LOW, MEDIUM, and HIGH risk labels
- Per-rule evidence so you can see why a repo was flagged, not just a black-box score
- PyPI package fake-star-audit v0.1.2 with uvx runtime hint and stdio MCP
- Transparent heuristics—no proprietary star-buying database required
- GitHub: ardev-lab/fake-star-audit
- Three risk levels: LOW, MEDIUM, HIGH
- Server version 0.1.2 on PyPI registry
- stdio MCP; runtimeHint uvx; repository ardev-lab/fake-star-audit
What problem does it solve?
You pick tools from star counts alone and cannot tell which trending repos bought engagement instead of earning it.
Who is it for?
Indie builders vetting GitHub repos for MCP servers, npm/pypi packages, or skills catalog entries during early research.
Skip if: Private repos without public star history, non-GitHub hosts, or legal due diligence that needs maintainer identity verification.
What do I get? / Deliverables
You get a labeled fake-star risk level with rule-by-rule evidence so you can skip or dig deeper before committing to a repo.
- LOW/MEDIUM/HIGH fake-star risk classification
- Per-rule evidence breakdown for the assessed repo
- Research notes your agent can cite when comparing dependencies
Recommended MCP Servers
Journey fit
Trust checks on GitHub signals belong in Idea research when you are discovering libraries, MCP servers, and skills to bet your product on. research is where you compare repos and community proof; fake-star audit adds evidence-backed reputation scoring to that discovery step.
How it compares
GitHub reputation heuristic MCP, not a full dependency CVE scanner or skills.sh install leaderboard.
Common Questions / FAQ
Who is fake-star-audit for?
Solo builders and agents researching open-source repos who want evidence-backed fake-star risk before adopting a dependency or MCP server.
When should I use fake-star-audit?
Use it during Idea research or Validate scoping when a repo’s star count looks too good versus issues, commits, or contributor patterns.
How do I add fake-star-audit to my agent?
Run the PyPI package fake-star-audit (uvx runtime hint) as a stdio MCP server in your client per registry entry version 0.1.2.