"A security license quality system or service" matching MCP servers:

Enables coding agents to turn OpenSpec intents and Git changes into revision-bound proofs by planning, selecting, and running the smallest safe protection set, then verifying composite verdicts and explaining evidence or unresolved states.

Automates repository analysis, test planning, and generation of end-to-end tests with Playwright, acting as an intelligent quality assistant.

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Generates precise, measurable quality evaluation standards and scoring criteria for any task, transforming vague requirements into specific dimensions that guide execution and improve work quality.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

Hybrid code quality analysis server combining fast logic-based checks with AI-powered deep analysis, offering tools for summaries, quick wins, and trend tracking.

Enables comprehensive video quality analysis including metadata extraction, GOP structure analysis, quality metrics comparison (PSNR, SSIM, VMAF), artifact detection, and transcoding effect assessment through FFmpeg-based tools.

Enables running SQL warehouse validation checks through natural-language questions in MCP clients, while reusing the same logic for automated pipeline and CI/CD runs.

Connects AI coding assistants to PyCharm's code quality inspections and optionally SonarQube for IDE, providing unified, de-duplicated code analysis results without uploading source code.

An MCP server that deterministically scores landing pages on conversion-critical signals and blocks ad spend on low-quality pages to prevent wasted budget.

Enables comprehensive security scanning of code projects, detecting vulnerabilities in dependencies, code patterns (XSS, eval, etc.), and exposed secrets, with detailed reports in Spanish prioritized by severity.

Enables AI assistants to scan project dependencies and Infrastructure as Code files for security vulnerabilities and misconfigurations. It also provides automated fixing capabilities to remediate identified security issues.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

A lightweight MCP server for security reviews that injects security requirements before code generation, scans dependencies for CVEs, and verifies generated code without disrupting workflow.

Analyzes API requirements and source code, evaluates existing Postman test coverage, and generates or updates test automation with an optional draft pull request on GitHub.

Automatically detects security vulnerabilities in AI-generated code, scanning for hardcoded secrets, injection flaws, XSS, weak cryptography, authentication issues, path traversal, and vulnerable dependencies across JavaScript, Python, Java, and Go.

Detect live website vulnerabilities and security flaws in GitHub repositories using automated DAST and SAST scanning. Safeguard applications by identifying exposed secrets, insecure dependencies, and common code patterns prone to exploitation. Receive structured fix plans with precise code remediation steps to resolve identified risks and improve security posture.

MCP server for Jama Connect that brings requirements, traceability, tests, and baselines into MCP clients like Claude, Cursor, VS Code, or GitHub Copilot, with access control, audit trail, and rate limiting. It provides 53 tools across 8 individually enableable toolsets, with an admin dashboard for managing access and usage.

Automatically discovers and tests MCP services for security vulnerabilities including command injection, SQL injection, SSRF, path traversal, and sensitive data exposure with detailed reports and remediation guidance.

Enables automated WCAG 2.2 AA accessibility audits of Figma designs and webpages. Generates detailed markdown reports with severity-grouped violations, specific criterion references, and concrete fix recommendations.