mighty-security
CLI/tooling to scan and analyze MCP servers for potentially malicious behavior (e.g., command injection, SSRF, credential/env leakage, path traversal). Includes an optional LLM mode (Cerebras) and mentions a web dashboard for monitoring/scans and exporting reports.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
Strengths (from README): mentions safe error handling (no info disclosure), URL/domain whitelisting, input validation/sanitization, rate limiting, and security headers for the dashboard. Risks/unknowns: no concrete evidence of TLS/auth for any remote service; optional LLM mode implies transmitting scan data to an external provider; no explicit guarantees about not logging secrets or handling sensitive inputs safely. Dependency hygiene cannot be verified from provided content; the dependency list is substantial and includes web/async frameworks, so supply-chain review is recommended.
⚡ Reliability
Best When
You are evaluating third-party MCP servers you did not author, and you can run the scanner in an isolated environment (and optionally enable LLM analysis) before installation/deployment.
Avoid When
You need strong guarantees of zero false positives or zero missed issues, or you cannot afford the risk of scanning untrusted code in an environment with any sensitive credentials/files.
Use Cases
- • Pre-install / pre-integration security scanning of MCP servers
- • CI checks for MCP server code or repositories (non-zero exit on findings)
- • Risk triage and threat reporting for third-party MCP tooling
- • Runtime monitoring/proxy monitoring to catch suspicious behavior (basic, per README)
Not For
- • Running MCP servers in production without a sandbox and additional controls
- • Auditing MCP server behavior at runtime without isolation (tooling may still expose sensitive data if misconfigured)
- • Compliance-grade assurance (no evidence of formal attestations, pen test reports, or audited guarantees)
Interface
Authentication
No authentication mechanism described for accessing an API service. LLM mode requires providing a Cerebras API key (per README), implying use of external credentials, but no auth scheme for the scanner itself is documented.
Pricing
No pricing information provided.
Agent Metadata
Known Gotchas
- ⚠ As a scanner, it may perform operations that can be risky with untrusted input; agents should run it in a sandbox and avoid sending sensitive data.
- ⚠ README suggests optional LLM analysis and a dashboard, but no stable programmatic API contract (schemas, endpoints, structured outputs) is described for agent integration.
- ⚠ Rate limiting is mentioned for local/GitHub scans, but there’s no documentation of headers, error codes, or retry guidance for API/automation flows.
Alternatives
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Scores are editorial opinions as of 2026-03-30.