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Alternatives to secretscan-mcp

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    Related Servers

    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI agents to inspect git working trees and history for exposed credentials without letting raw secrets reach the model, with false-positive filtering, baseline support, and remediation guidance.
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI agents to autonomously scan repositories and staged changes for leaked secrets, move exposed credentials into environment files, purge secrets from Git history, and verify remediation through deterministic tools.
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents to scan code or text content for hardcoded API keys, passwords, tokens, and private keys, reporting each finding by type, confidence, key name, and position. Secret values are never returned, so credentials can be located and addressed without leaving the machine.
      20 npm
      1
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents to scan a repository or project for malware, supply-chain attacks, leaked secrets, and web, server, cloud, and CI/CD vulnerabilities, then confirm real findings with concrete attack scenarios and fixes. Exposes scan, guide, and reference tools plus a security-review prompt that runs locally.
      1
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables scanning arbitrary text and added lines in unified git diffs for accidentally committed credentials, using precise vendor-format matches and entropy-based detection. All detected secrets are redacted before results are returned, helping coding agents and developers catch leaks without exposing full values.
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Enables scanning diffs or code blobs for leaked secrets, returning a verdict with severity and masked findings, all processed locally with no data sent externally.
      1
      MIT

    Maintenance

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