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Alternatives to mahrem-mcp

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    Related Servers

    • A
      license
      A
      quality
      A
      maintenance
      Enables an AI assistant to redact text and, more importantly, files without reading them, since file redaction and restoration happen locally and only counts are reported, keeping personal data out of the conversation. It exposes tools for redacting text, writing a redacted copy of a UTF-8 file with an owner-only restore mapping, and putting original values back offline.
      3
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to browse and read files from allowlisted folders while names, IDs, contacts, and secrets are replaced with consistent tokens locally before the agent ever sees them. The agent's final answer can then be restored to the original values locally, with no write tools and no file contents leaving the machine.
      59 npm
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables irreversible anonymisation of documents and spreadsheets (PDF, Word, PowerPoint, HTML, Excel, CSV) into consistent pseudonymised Markdown before they reach an AI, keeping names, national IDs, bank details and contact data unrecoverable. Runs as a free online HTTP endpoint needing no key, or locally with the full engine bundled so nothing leaves the machine.
      MIT
    • F
      license
      Not graded
      quality
      B
      maintenance
      Enables Claude to work on documents containing personal data by pseudonymizing names, addresses, IBANs, health data and other GDPR categories locally before they are sent, then restoring the real values on your own machine. Supports Word, Excel, PowerPoint, PDF, CSV, Markdown, e-mail and other formats with consistent pseudonyms per project and no data leaving the computer.
      -
    • A
      license
      A
      quality
      A
      maintenance
      Lets AI assistants work on sensitive files by reasoning over schemas and masked output while deterministic local code handles raw data, never exposing real values to the model.
      5
      30 PyPI
      MIT
    • A
      license
      A
      quality
      A
      maintenance
      Sanitizes text and files by removing PII, secrets, and custom patterns locally before sending to LLMs, with optional reverse-scrubbing.
      3
      1,136 npm
      146 PyPI
      3
      MIT

    TDQS

    B3.3/5.0

    Scored across 4 tools

    Disambiguation5/5

    Each tool maps to a distinct stage in the masking workflow: scan for warnings, mask to produce placeholders, restore to reinsert values, and forget to clean up session state. Although scan and mask both operate on local files, their outputs and purposes are clearly differentiated.

    Naming Consistency5/5

    All four names follow a consistent snake_case verb_noun pattern (scan_file, mask_file, restore_file, forget_session), making the set predictable and easy to navigate.

    Tool Count5/5

    Four tools is well-scoped for a focused privacy-preserving file workflow; each tool earns its place without redundancy.

    Completeness4/5

    The set covers the core lifecycle of scan, mask, restore, and cleanup, but lacks any tool to list or inspect active sessions/placeholder mappings, which could be a minor gap for multi-file use.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues