Runs three filesystem scans to catch secrets before your AI agent sees them: hardcoded credentials across 20+ patterns (AWS keys, Stripe tokens, database URLs, JWTs), console.log statements that dump environment variables or config objects at runtime, and sensitive files missing from .gitignore. Returns masked previews with severity ratings and line numbers, never the actual values. Built for the specific risk of helpful agents accidentally ingesting credentials during debugging sessions or config reviews. Works entirely locally via stdio, no secrets leave your machine. Pairs well with CI readiness and code analysis servers if you're building pre-commit or pre-release guardrails into agent workflows.
Your AI agent is one debug session away from leaking your secrets.
MCP server that scans your project for secret exposure risks — hardcoded API keys, unprotected .env files, and console.log calls that print credentials at runtime. Before your agent accidentally reads them out loud.
You ask your AI agent to debug a config issue. It reads src/config.ts. Inside:
console.log('Config loaded:', JSON.stringify(config));
console.log(process.env.DATABASE_PASSWORD);
The agent now has your database password in its context. It might log it, include it in a summary, or pass it to another tool. And your .env isn't in .gitignore, so the next git push will do the rest.
None of this requires the agent to be malicious. It just needs to be helpful.
env-secret-exposure-analyzer-mcp catches this before it happens. 🔐
scan_for_secretsScans source files, config files, and .env files for 20+ secret patterns. Returns file path, line number, severity, and a masked preview — never the full value.
Detects:
ghp_, gho_, ghs_)whsec_)SG.xxx), Twilio auth token + account SIDGOCSPX-)xox*)-----BEGIN ... PRIVATE KEY-----)postgres://user:pass@host)Secret Scan Results
Project: /project
Files scanned: 24
Findings: 5
[CRITICAL] .env:3 — AWS Access Key
Preview: AKIA****MPLE
[CRITICAL] .env:7 — Database URL with password
Preview: post****sswd
[CRITICAL] src/auth.ts:12 — Hardcoded JWT secret
Preview: my-s****ecret
[HIGH] .env:14 — Hardcoded session secret
Preview: sess****key!
[MEDIUM] .env:28 — Sentry DSN
Preview: http****7890
check_gitignore_coverageChecks whether sensitive files (.env, .env.local, secrets.json, private keys, certificates) are covered by .gitignore. Flags files that could be accidentally committed.
Gitignore Coverage Check
Project: /project
✗ .env → Add to .gitignore: .env
✗ .env.local → Add to .gitignore: .env.local
✓ secrets.json
scan_for_log_leaksScans source files for console.log / logger calls that print process.env variables or objects with secret-sounding names at runtime. Catches the most common "it's just a debug line" mistakes.
Log Leak Scan
Project: /project
Files scanned: 18
Findings: 3
[CRITICAL] src/config.ts:8
console.log("Config loaded:", JSON.stringify(config));
[HIGH] src/server.ts:42
console.log(process.env.AWS_SECRET_ACCESS_KEY);
[HIGH] src/db.ts:15
logger.info({ password: dbConfig.password });
A realistic .env with 20 secrets — database URLs, AWS, Stripe, Twilio, SendGrid, Google OAuth, Sentry, JWT secrets, encryption keys. Before this MCP: an AI agent reads the file, has no idea what's sensitive, and proceeds to use those values in generated code or responses.
After one scan_for_secrets call: 16 findings, all categorized by severity, all previews masked. The agent knows exactly what's dangerous before it touches anything.
{
"mcpServers": {
"secret-scanner": {
"command": "npx",
"args": ["-y", "env-secret-exposure-analyzer-mcp"]
}
}
}
"Scan this project for any secrets or API keys that might be exposed. Check if .env files are in .gitignore, and look for any console.log calls that might be leaking credentials."
The agent runs all three tools in sequence and reports a full picture: what's hardcoded, what's not protected, what's being logged.
Works great alongside:
MIT