"Orbit Sentinel - Satellite or Space Monitoring System" matching MCP servers:

Enables MCP clients to scan tool manifests and server configs for prompt injection, tool poisoning, excessive agency, and other OWASP-mapped security issues directly through the scan_mcp_manifest tool.

Enables AI agents and software engineers to investigate and resolve realistic distributed-system incidents using safe MCP-based diagnostic tools for code, logs, metrics, traces, database, and deployments.

An MCP server for AI-powered API testing that enables automated positive, negative, and security testing directly from AI chat interfaces. It supports multiple AI providers and generates detailed security reports.

Provides LLMs and AI agents safe, structured, read-only access to verification artifacts for deterministic triage and root-cause analysis. Supports UVM, cocotb, and SystemVerilog verification ecosystems.

Enables AI assistants to interact with Godot game projects through real-time error detection, automated testing, code analysis, and safe git-based patching. Provides comprehensive project context and development workflow automation for Godot developers.

Sentinel is an enterprise-grade security server that integrates tools like Semgrep, Trivy, and Gitleaks via Docker to perform automated vulnerability scanning and compliance checks. It enables users to conduct static analysis, secret detection, and AI-powered threat modeling directly through Model Context Protocol-compatible IDEs.

A code quality analysis server that detects security vulnerabilities, deceptive patterns, incomplete code, and highlights good practices in source code for MCP-compatible clients like Claude Code.

Provides real-time TBC Bank development standards compliance checking and code review tools. Integrates with GitHub Copilot and development workflows to automatically enforce coding guidelines and reduce violations.

Enables intelligent analysis of regression test failures and automatic discovery of solutions in JIRA. Analyzes test logs using AI-driven algorithms and matches errors with relevant JIRA issues through natural language interactions.

Self-healing test automation MCP server that diagnoses and fixes issues in mobile and web apps, including a one-command vibe-check to prioritize broken functionality.

Enables AI agents to access observability and evaluation data, including run history, span traces, LLM-as-judge evaluation results, and regression reports.

Provides self-healing UI/API test automation via Plan-Generate-Run-Heal cycle, exposing MCP tools for test platforms to trigger batches and retrieve reports.

Enables LLMs to read existing PageSnap session packs and map locators to Playwright, Selenium, or Cypress without capturing or opening a browser.

Generates realistic, referentially-coherent test data (SQL INSERTs, JSON, or CSV) from your database schema, resolving foreign keys and respecting constraints. Paste CREATE TABLE DDL or a JSON schema and get ready-to-run seed data with valid relationships.

Adversarial review system that spawns three independent contrarian reviewers to catch issues before AI coding agents execute critical changes.

MCP server for IFC geometric audit, providing tools to detect space clashes, extract space inventories, compute surface losses, check boundaries, and verify opening correspondences in BIM models.

Multi-engine container and system vulnerability scanning for AI agents. Wraps Trivy and Grype with cross-engine validation, SBOM generation, and IaC misconfiguration scanning.

MCP server for Beaker lab automation, enabling system provisioning, job management, distro discovery, and failure diagnosis through 25 tools.

QA Sphere MCP server that enables Large Language Models to interact directly with test management system test cases, supporting AI-powered development workflows and test case discovery.

Enables AI assistants to interact with Coval's evaluation platform for launching and monitoring evaluation runs, managing agents and test sets, and retrieving evaluation metrics.