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Prompt Shield & AI Safety MCP

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    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables scanning LLM prompts and responses for prompt injection, jailbreaks, PII leakage, secret leakage, and other malicious content using deterministic rules, returning verdicts and safe redacted text.
      1
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Protects AI agents from threats like prompt injection, jailbreaks, and SQL injection through a multi-layer scanning pipeline. It also enables PII redaction and rehydration to ensure data privacy during LLM interactions.
      12
      318 npm
      2
      Apache 2.0
    • F
      license
      Not graded
      quality
      D
      maintenance
      Security middleware for LLM apps and AI agent pipelines. Detects prompt injection attacks (22 signatures, 7 languages) and anonymizes PII (17 entity types). Deterministic, sub-25ms, GDPR Art.30 compliant.
      -
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables deterministic zero-trust security for AI agents, providing prompt injection protection, PII scrubbing, and policy enforcement before agentic actions reach production systems.
      2
      Apache 2.0
    • A
      license
      Not graded
      quality
      D
      maintenance
      Analyzes inputs and outputs in real-time to protect against prompt injections, data leaks, secrets exposure, and phishing URLs.
      10 npm
      3
      MIT
    • A
      license
      Not graded
      quality
      D
      maintenance
      Provides a pre-flight/post-flight firewall for LLM calls with comprehensive detection, classification, policy enforcement, reversible redaction, output safety, and immutable audit logging.
      1
      MIT

    TDQS

    A3.5/5.0

    Scored across 5 tools

    Disambiguation4/5

    Most tools target clearly distinct safety functions: PII masking, bias auditing, injection detection, injection neutralization, and secrets scanning. The two prompt-injection tools could be confused at a glance, but their descriptions distinguish detection/classification from stripping/neutralization.

    Naming Consistency3/5

    All names use snake_case and are descriptive, but the structural pattern is mixed: some are verb-first (obfuscate_pii_entities, strip_prompt_injection) while others are noun phrases ending in auditor/classifier/scanner. This is readable but not a predictable convention.

    Tool Count5/5

    Five tools is well within the sensible range for a focused AI safety/prompt shield server. Each tool covers a distinct guardrail capability, so none feels redundant or extraneous.

    Completeness4/5

    The surface covers key input-side guardrails: PII, bias, prompt injection detection/removal, and secrets scanning. Minor gaps remain around output-side moderation, toxicity classification, or policy enforcement, but the core lifecycle for a prompt safety server is reasonably covered.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues