"Improving OKR Strategies" matching MCP servers:

Protects AI agents from prompt injection and destructive actions while enabling self-improving prompts through a security pipeline.

An MCP server that enables LLMs to detect and anonymize over 25 types of Personally Identifiable Information (PII) using Microsoft Presidio. It supports various redaction strategies and can process both plain text and structured data to help ensure data privacy.

AI-powered sensitive info detection and masking MCP server supporting 14+ types with regex, checksum, and optional LLM semantic detection, enabling flexible masking strategies like mask, replace, hash, and redact.

Detects and redacts sensitive personal information such as names, emails, phone numbers, ID numbers, and locations in text before it is processed by AI agents, using configurable mask, hash, or remove strategies.

An MCP server for identifying SQL injection vulnerabilities in web applications using various techniques like error-based, time-based, and union-based scanning. It supports bulk URL processing, WAF bypass strategies, and authenticated testing across multiple database systems.

Enables security scanning of code projects to identify common vulnerabilities like XSS, injections, SSRF, and path traversal issues. Provides local, offline scanning with severity-grouped results and actionable fix suggestions for improving code security.

Enables AI-assisted security assessments by scanning URLs for SQL injection vulnerabilities using error-based, boolean-based, and time-based detection strategies.

Security-focused MCP adapter that combines read-only DataHub metadata with a reviewed OKF-derived policy IR to execute closed, typed SQL queries against synthetic PostgreSQL data.

Unified MCP server integrating NIST and OWASP security frameworks with live vulnerability data, enabling security searches, compliance mapping, threat modeling, and checklist generation.