io.github.salrad22/code-sentinel

MCPcommunity
v0.2.6io.github.salrad22UnknownUpdated 6mo agonpmGitHub

Code quality analysis MCP server - detects security issues, deceptive patterns, and placeholders

A comprehensive code quality analysis server for the Model Context Protocol (MCP). CodeSentinel integrates with Claude Code and other MCP-compatible clients to detect security vulnerabilities, deceptive patterns, incomplete code, and highlight good practices. AI coding assistants can inadvertently introduce subtle issues: hardcoded secrets, empty catch blocks, TODO placeholders left behind, or…

Automatically indexed from public sources. Not yet verified by the developer on Forge.Claim this listing →
6mo agoLast update
Package
Authorio.github.salrad22
LicenseUnknown
Version0.2.6
Sourcemcp-registry
npmcode-sentinel-mcp
GitHubsalrad22/code-sentinel
Trust Status
B
60/100Good
✓Listed in Forge index+10/10
—Publisher identity verified+0/25
→ Publisher: run `forge publish` from the package repo to claim ownership
—Ed25519 publish signature+0/10
→ Included automatically when the publisher runs `forge publish`
—Domain verification+0/5
→ Publisher: host /.well-known/forge.json on the package homepage with { "publisher": "<github-login>" }
✓CVE scan · clean+30/30
✓Static analysis · clean+20/20
—npm provenance (Sigstore)+0/5
→ Publish from GitHub Actions with the --provenance flag
Paste into Claude Code, Cursor, or any AI assistant to fix all gaps
StatusCommunity-indexed
PublisherUnverified
SignatureUnsigned
Domain—
Provenance—
Dependencies✓ 60 resolved+ · none vulnerable
Tool surface14 tools · none privileged
Security scan✓ Cleanv0.2.6 · 20d ago
EvalsNone
IndexedJun 13, 2026

Verification confirms publisher identity (repo ownership), not code safety. The security scan covers known CVEs and suspicious install scripts — it cannot prove the absence of malicious code.

About

A comprehensive code quality analysis server for the Model Context Protocol (MCP). CodeSentinel integrates with Claude Code and other MCP-compatible clients to detect security vulnerabilities, deceptive patterns, incomplete code, and highlight good practices. AI coding assistants can inadvertently introduce subtle issues: hardcoded secrets, empty catch blocks, TODO placeholders left behind, or patterns that hide errors. CodeSentinel acts as a quality gate, analyzing code for 93 distinct…

Keywords
mcp