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    Connects AI coding assistants to Gaffer test history and coverage data to analyze project health, debug failures, and identify untested code areas. It enables tools to track test stability, cluster failures by root cause, and monitor code coverage trends across projects.
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    MIT
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    An MCP server that enables AI assistants to interact with Apache Airflow's REST API for DAG management, task monitoring, and system diagnostics. It provides comprehensive tools for triggering workflows, retrieving logs, and inspecting system health across Airflow 2.x and 3.x versions.
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    Apache 2.0
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    Enables inspection and management of Apache Airflow DAGs, runs, and logs across multiple instances. It provides tools for monitoring workflows and performing gated write operations like triggering DAGs or clearing task instances.
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    Apache 2.0
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    Enables monitoring and analysis of Ansible playbook executions through the Ara Records API. Provides real-time playbook monitoring, task progress tracking, and comprehensive access to Ansible execution data.
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    Enables management of Amazon Managed Workflows for Apache Airflow (MWAA) environments and operations including DAG management, workflow execution monitoring, and access to Airflow connections and variables through a unified interface.
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    Apache 2.0
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    Enables AI assistants to interact with Coolify self-hosted instances for application deployment, management, and monitoring. Features 4 unified tools optimized for VS Code's limits, covering app management, environment configuration, system administration, and built-in documentation.
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    MIT
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    Enables comprehensive Jenkins automation through MCP interface, allowing users to manage builds, jobs, artifacts, and queues with natural language commands. Supports build triggering, monitoring, artifact retrieval, and system status checks with automatic CSRF protection and authentication.
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    MIT
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    Enables comprehensive Datadog monitoring capabilities including CI/CD pipeline management, service logs analysis, metrics querying, monitor and SLO management, service definitions retrieval, and team management through Claude and other MCP clients.
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    A TypeScript starter template for building Model Context Protocol (MCP) servers with built-in support for tools, testing, and CI/CD pipelines. It provides a complete development environment for creating custom AI assistant integrations for tools like Claude, Copilot, and Cursor.
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    MIT
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    A TypeScript-based MCP server scaffold designed for monitoring and interacting with Drone CI environments. It provides tools for webhook parsing, HMAC signature verification, and state management for CI/CD pipelines.
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    Apache 2.0
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    Enables AI assistants to interact with and manage Google Cloud Platform resources including Artifact Registry, BigQuery, Cloud Build, Compute Engine, Cloud Run, Cloud Storage, and monitoring services through a standardized MCP interface.
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