Enables automated testing and coverage reporting for MCP services with test execution, file generation, and mock service creation. Provides comprehensive testing infrastructure including Jest integration, coverage reports, and health checks for the MCP ecosystem.
An MCP server that executes tox commands to run Python tests within a project using pytest, allowing users to run all tests or specific test groups, files, cases, or directories.
A multi-language testing automation server that enables AI assistants to discover, plan, and execute tests across six major programming languages. It provides comprehensive tools for repository scanning, automated test execution, and detailed coverage reporting.
Provides AI agents with 25 security analysis tools including vulnerability scanning, package hallucination detection, prompt injection firewall, and CI/CD integration.
Automates 85-95% of the Secure Software Development Lifecycle (SSDLC) planning phase through multi-role AI orchestration, enabling business analysis, threat modeling, test strategy design, and security code review.
A specialized MCP server for QA engineering. It provides tools for user story analysis, test strategy, BDD/Gherkin scenarios, contract testing, integration tests, performance plans, security checklists, and CI/CD pipeline generation, accessible from any MCP-compatible IDE or client.
Enables interaction with Azure DevOps through natural language in Cursor IDE. Supports work item management, pull requests, builds, releases, test management, and guided workflows for development teams, QA testers, and release management.
Orchestrates end-to-end testing of AI-powered incident remediation workflows through declarative YAML scenarios, fault injection, AI response evaluation, and automated command execution with comprehensive reporting.
Enables orchestrating secure software development pipelines with domain-specific compliance (HIPAA, PCI-DSS, etc.), generating pseudocode, threat models, and CI/CD from user stories via natural language.
A Model Context Protocol server implementation that allows AI models to interact with and manage Spinnaker deployments, pipelines, and applications through a standardized interface.
A remote MCP server that provides AI agents access to the Rootly API for incident management, allowing users to query and manage incidents, alerts, teams, services, and other incident management resources through natural language.