claude mcp add cleaner-code -- npx -y cleaner-code
A pasteable skeleton generated from the repository name. Check the project README for the exact package and arguments.
Star count
1 ★ · goldmembrane/cleaner-code · read from the GitHub search API · (checked 2026-10-16 20:00:20)
Source
collected from the punkpeye/awesome-mcp-servers list · type: MCP server
Harvest history
first seen 2026-10-09 · last seen 2026-10-16 · seen 32× · listed by 7 sources
Score
score 703 · 1 ★ · 7 sources · mcp
FAQ (answers come from our records)
How do I install it?
We did not find an install command for this repository (our install coverage is only about 4%). Check its README or releases page.
Who is it for?
We filed it under these tags: MCP 服务. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
repository goldmembrane/cleaner-code;first catalogued 2026-10-09;last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.
> **AI code security scanner as a Model Context Protocol (MCP) server.** > Detects hidden threats in AI-generated code that traditional linters miss. **Website:** codesafer.org · **MCP Clients:** Claude Code, Cursor, VS Code + Copilot, Cline --- Why CodeSafer? AI coding assistants generate code fast — but who's checking it for hidden threats? Recent supply-chain attacks show that malicious code can hide in ways human reviewers and traditional linters routinely miss: - **Invisible Unicode characters** injected into identifiers (30+ variants) - **BiDi / Trojan Source** attacks that reorder how code is displayed vs. executed (CVE-2021-42574) - **Homoglyphs** — Cyrillic characters masquerading as Latin (CVE-2021-42694) - **Glassworm-style Unicode steganography** hiding payloads in whitespace - **Rules file backdoors** planted in .cursorrules, CLAUDE.md, and other AI config files - **Typosquatted dependencies** in package.json - **Obfuscation patterns** — eval + base64, reverse shells, packed payloads CodeSafer scans for all of these before the code runs on your machine. --- How it works CodeSafer runs as a local MCP server. Your AI client (Claude Code, Cursor, etc.) calls its tools when reviewing or generating code, and findings are returned inline. **Hybrid detection:** 1. **8 static analysis scanners** — deterministic rules for known attack categories (fast, zero false-negatives on the patterns they cover). 2. **CodeBERT deep analysis** — transformer model classifies code chunks as malicious/benign with confidence scores. Catches obfuscated or novel patterns that static rules miss. Nothing leaves your machine. The AI analysis runs locally against a tokenizer server. --- Features | Capability | Details | |---|---| | Invisible character detection | 30+ Unicode variants including Zero-Width Space, Mongolian Vowel Separator | | BiDi / Trojan Source | Full CVE-2021-42574 coverage | | Homoglyph detection | Cyrillic/Greek/Latin confusables (CVE-2021-42694) | | Unicode steganography | Glassworm-style whitespace payloads | | Rules file backdoors | Scans .cursorrules, CLAUDE.md, .claude/, Cursor rules | | Dependency scanning | Typosquatting + suspicious install scripts in package.json | | Obfuscation detection | eval + base64, reverse shells, packed payloads | | AI deep analysis | CodeBERT transformer classifier with confidence scores | | MCP native | 6 MCP tools, stdio transport | | Local-first | No code uploaded — runs entirely on your machine | --- MCP Tools CodeSafer exposes six tools to your MCP client: | Tool | Purpose | |---|---| | scan_file | Scan a single file for hidden malicious code patterns | | scan_directory | Recursively scan a directory across all source files | | scan_rules_file | Scan an AI configuration/rules file for prompt injection and Rules File Backdoor attacks | | check_dependencies | Check package.json for typosquatting, suspicious install scripts, and dependency risks | | ai_analyze | Deep AI analysis using the trained CodeBERT model (classifies chunks as malicious/benign with confidence) |