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Alternatives to prompt-injection-mcp

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    Related Servers

    • A
      license
      B
      quality
      D
      maintenance
      Enables testing AI safety classifier robustness against query decomposition, obfuscation, and multi-agent attacks. Provides tools for full evaluation pipelines, query previews, and status checks.
      4
      6
      MIT
    • A
      license
      B
      quality
      C
      maintenance
      Provides local, dependency-free security scanning tools for LLM configurations, prompts, RAG sources, and more, enabling AI coding agents to detect prompt injections and other vulnerabilities without external network access.
      8
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables users to scan untrusted text, files, and directory trees for prompt-injection patterns and receive severity-ranked, explainable verdicts before content reaches an agent. It runs locally and returns clean, review, or blocked verdicts for safer agent input.
      MIT
    • A
      license
      B
      quality
      D
      maintenance
      Enables security teams to run controlled adversarial penetration tests against authorized ML/LLM API endpoints, scoring responses and generating evidence for compliance frameworks such as SOC 2, ISO 27001, and GDPR.
      6
      2
      MIT
    • F
      license
      Not graded
      quality
      B
      maintenance
      Enables guardrail and trust testing by exposing realistic malicious tool patterns such as shell execution, credential dumping, and data exfiltration, all without network access.
      -

    TDQS

    B3.2/5.0

    Scored across 8 tools

    Disambiguation4/5

    Each tool targets a distinct phase of the testing workflow: listing categories, retrieving payloads (by category, ID, or keyword), generating custom payloads, running tests, analyzing responses, and reporting. Minor overlap exists between search_payloads and get_payloads_by_category, but their scopes and verbs are clearly differentiated.

    Naming Consistency5/5

    All tool names use consistent snake_case and follow a verb_noun or verb_noun_preposition pattern (list_, get_, run_, generate_, analyze_, search_). No conventions are mixed.

    Tool Count5/5

    8 tools cover the entire prompt-injection testing lifecycle without redundancy. Each tool maps to a natural workflow step, making the set lean yet sufficient.

    Completeness4/5

    The core workflow from payload discovery to report generation is fully covered. Missing management operations for payloads (update/delete) and test sequences, but the read/generate/run/analyze path is complete for typical testing use.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues