Stript MCP Bridge
Related Servers
Alternatives to Stript MCP Bridge
No user-submitted related servers found.
Related Servers
- AlicenseAqualityAmaintenanceSanitizes text and files by removing PII, secrets, and custom patterns locally before sending to LLMs, with optional reverse-scrubbing.3507 npm2Cryptographic Autonomy 1.0 (Combined Work Exception)
- AlicenseAqualityDmaintenanceProvides local anonymization of Czech legal documents by replacing sensitive entities with pseudonyms to ensure privacy during LLM interactions. It allows users to safely process documents like contracts and judgments by keeping original data offline and facilitating local deanonymization.55MIT
- AlicenseBqualityCmaintenanceEnables AI assistants to mask personal data in local Turkish documents by accepting a local file path (TXT, MD, DOCX, or text PDF) and returning pseudonymized text such as [KISI-1] and [TCKN-1] instead of the original values. Tools scan for PII types, produce masked output, and restore real values into a local file without ever returning plaintext to the model.41MIT

Strac MCP DLPofficial
AlicenseAqualityAmaintenanceDetect and redact PII, PHI, PCI and secrets — SSNs, credit cards, passports, API keys and cloud credentials — in text and in local files, using the Strac DLP API. Five tools: redact_text, detect_sensitive_data, detect_file, redact_file and detokenize.57MIT- AlicenseAqualityDmaintenanceScans prompts for PII and masks or redacts sensitive data locally before sending to an LLM, supporting multiple anonymization modes.1MIT
- AlicenseAqualityCmaintenanceProvides AI agents with local file-processing capabilities for token counting, RAG chunking, CSV/JSON conversion, QR generation, and more, while keeping documents private on the user's machine.71MIT
TDQS
Scored across 5 tools
The tools are largely distinct: anonymize_file initiates new processing, fetch_result retrieves existing results, restore and restore_file handle inverse operations for text and files, and status checks the app state. Some minor overlap exists between anonymize_file and fetch_result (both return anonymized content) and between the two restore tools, but the descriptions provide sufficient differentiation.
All tools share the 'stript_' prefix and use snake_case, but the pattern is inconsistent: most are verb_noun (stript_anonymize_file, stript_fetch_result, stript_restore_file), while stript_restore lacks an object and stript_status is a noun rather than a verb. This makes the naming somewhat predictable but not uniform.
With 5 tools, the server is well-scoped for its purpose: anonymize, fetch result, restore (both text and file), and check status. This is within the ideal 3-15 range and each tool serves a necessary step in the Stript workflow without unnecessary bloat.
The tool set covers the full lifecycle: anonymizing files, fetching results (including waiting for review), restoring placeholders in AI responses or files, and checking system status. There are no obvious dead ends or missing operations for the stated purpose of bridging Stript anonymization into MCP.