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    Enables AI assistants to interact with Jenkins CI/CD systems through natural language, providing build management, job monitoring, log analysis, and debugging capabilities.
    MIT
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    MCP server that lets coding agents test AI agents. Create YAML test cases, snapshot golden baselines, check for regressions, and generate visual reports all from inside Claude Code or any MCP-compatible tool. Works with LangGraph, CrewAI, OpenAI, Claude, Mistral, and any HTTP API.
    10
    29
    128
    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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    Multi-persona engineering mentor with 64 specialized AI personas that injects engineering standards before Claude reasons, transforming passive documentation into active collaborative guidance.
    25
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    Apache 2.0
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    An MCP server that enables AI-powered IDEs to implement a structured development workflow from requirements gathering to code implementation, guiding users through goal collection, requirements specification, design documentation, task planning, and execution.
    9
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    MIT
  • F
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    Enables issue-to-code automation for GitHub and GitLab by connecting AI assistants (Claude Code, Gemini CLI, Codex) via MCP, with slash commands for issue analysis, planning, implementation, testing, documentation, and PR creation.
    33
    9
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    A secure, containerized MCP server that enables AI assistants to manage Terraform infrastructure using integrated Language Server Protocol (LSP) tools. It facilitates safe operations like initialization, validation, and planning while providing context-aware code completion and documentation.
    10
    MIT
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    A boilerplate for building FastMCP servers, providing a basic setup for testing, linting, formatting, and publishing to NPM.
    13
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    MIT
  • A
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    Provides Kubernetes deployment intelligence with typed query tools and AI-synthesized risk briefs, enabling users to list workloads, get detailed snapshots, query Prometheus metrics, record deployment history, and generate risk assessments before promoting to production.
    Apache 2.0
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    Enables intelligent Kubernetes deployments, automated documentation testing, organizational pattern management, and shared prompt libraries. Provides AI-powered recommendations based on cluster capabilities and automates DevOps workflows through conversational interfaces.
    724
    335
    MIT