"A server for test coverage and MCP integration" matching MCP servers:

Enables test execution and management through MCP clients, allowing retrieval of projects, listing tests, executing tests with browser selection, and monitoring results.

Facilitates unified execution and result parsing for various testing frameworks, including Bats, Pytest, Flutter, Jest, and Go, through a Model Context Protocol interface.

A test harness for MCP servers that validates server JSON, tool schemas, performs golden file diffing and schema drift detection, and generates signed test reports with Shields.io badges.

An end-to-end test MCP server built with FastMCP that exposes a REST API as a set of tools for AI agents. It enables LLMs to perform CRUD operations on an upstream API by mapping HTTP methods to MCP tools.

A minimal MCP server with greet, add, and whoami tools, designed to validate deployment pipelines and environment variable injection.

Provides AI-assisted guidance for the Weik.io integration platform, enabling planning, implementation, testing, and deployment of integrations using Apache Camel and specialized Weik.io features.

Monitor failing GitHub Actions workflows, auto-fix them with OpenCode, and retry the run — driven by a workflow_run webhook, coordinated through an MCP server.

A Model Context Protocol (MCP) server that provides Xcode-related tools for integration with AI assistants and other MCP clients.

Enables automatic generation of test scenarios from user stories uploaded to Claude desktop. Leverages MCP integration to streamline the test case creation process for development workflows.

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.

Enables managing SAP Cloud Integration iFlows, packages, configurations, deployments, and runtime artifacts via natural language through the OData API.

Provides a standardized way for MCP clients to interact with Apache Airflow's REST API, supporting operations like DAG management and monitoring Airflow system health.

Karpenter is a Kubernetes Node Autoscaler built for flexibility, performance, and simplicity.

A Model Context Protocol server implementation that allows AI models to interact with and manage Spinnaker deployments, pipelines, and applications through a standardized interface.

Provides integration with Apache Airflow's REST API, allowing AI assistants to programmatically interact with Airflow workflows, monitor DAG runs, and manage tasks.

Enables automated analysis of test suite traces to identify timing races and state pollution, helping detect flaky test non-determinism in CI/CD workflows such as Datadog CI or Trunk.

Enables querying Codecov coverage data including file, commit, repository, and pull request coverage.

Integrates Cline with Azure DevOps services, enabling access to work items, repositories, and pull requests through configurable MCP tools.

Provides AI assistants with comprehensive access to Azure DevOps services including work items, repositories, pull requests, wikis, builds, pipelines, and test plans through 25+ MCP tools with multi-project support.

Enables AI assistants to run Vitest tests and analyze code coverage, supporting test-driven development workflows with tools for test execution and coverage analysis.