[{"_1":2,"_336":-5,"_337":-5},"loaderData",{"_3":4,"_22":23,"_24":25,"_273":274},"root",{"_5":6,"_7":8},"toasts",[],"visitor",{"_9":10,"_11":12},"viewportWidth",1280,"visitorSession",{"_13":14,"_16":17,"_18":-5,"_19":20,"_21":-5},"attributes",[15],"BOT","id",7058884,"membership","referenceId","01971406-43e3-74e8-b880-2f000258007a","userAccount","routes/_public/_layout",{},"routes/_public/mcp/servers/~namespace/~slug/_pages/_layout",{"_26":27,"_68":-5,"_69":28,"_29":70,"_190":191,"_271":272},"availableLocales",[28,40,47,54,61],{"_29":30,"_33":37,"_38":39},"mcpServer",{"_31":32,"_33":34,"_35":36},"description","Simple MCP Server to enable a human-in-the-loop workflow in tools like Cline and Cursor. This is especially useful for developing desktop applications that require complex user interactions to test.","name","User Feedback","readme","# User Feedback MCP\r\n\r\nSimple [MCP Server](https://modelcontextprotocol.io/introduction) to enable a human-in-the-loop workflow in tools like [Cline](https://cline.bot) and [Cursor](https://www.cursor.com). This is especially useful for developing desktop applications that require complex user interactions to test.\r\n\r\n![Screenshot showing the feedback UI](https://github.com/mrexodia/user-feedback-mcp/blob/main/.github/feedback-ui.png?raw=true)\r\n\r\n## Prompt Engineering\r\n\r\nFor the best results, add the following to your custom prompt:\r\n\r\n> Before completing the task, use the user_feedback MCP tool to ask the user for feedback.\r\n\r\nThis will ensure Cline uses this MCP server to request user feedback before marking the task as completed.\r\n\r\n## `.user-feedback.json`\r\n\r\nHitting _Save Configuration_ creates a `.user-feedback.json` file in your project directory that looks like this:\r\n\r\n```json\r\n{\r\n \"command\": \"npm run dev\",\r\n \"execute_automatically\": false\r\n}\r\n```\r\n\r\nThis configuration will be loaded on startup and if `execute_automatically` is enabled your `command` will be instantly executed (you will not have to click _Run_ manually). For multi-step commands you should use something like [Task](https://taskfile.dev).\r\n\r\n## Installation (Cline)\r\n\r\nTo install the MCP server in Cline, follow these steps (see screenshot):\r\n\r\n![Screenshot showing installation steps](https://github.com/mrexodia/user-feedback-mcp/blob/main/.github/cline-installation.png?raw=true)\r\n\r\n1. Install [uv](https://github.com/astral-sh/uv) globally:\r\n - Windows: `pip install uv`\r\n - Linux/Mac: `curl -LsSf https://astral.sh/uv/install.sh | sh`\r\n2. Clone this repository, for this example `C:\\MCP\\user-feedback-mcp`.\r\n3. Navigate to the Cline _MCP Servers_ configuration (see screenshot).\r\n4. Click on the _Installed_ tab.\r\n5. Click on _Configure MCP Servers_, which will open `cline_mcp_settings.json`.\r\n6. Add the `user-feedback-mcp` server:\r\n\r\n```json\r\n{\r\n \"mcpServers\": {\r\n \"github.com/mrexodia/user-feedback-mcp\": {\r\n \"command\": \"uv\",\r\n \"args\": [\r\n \"--directory\",\r\n \"c:\\\\MCP\\\\user-feedback-mcp\",\r\n \"run\",\r\n \"server.py\"\r\n ],\r\n \"timeout\": 600,\r\n \"autoApprove\": [\r\n \"user_feedback\"\r\n ]\r\n }\r\n }\r\n}\r\n\r\n```\r\n\r\n## Development\r\n\r\n```sh\r\nuv run fastmcp dev server.py\r\n```\r\n\r\nThis will open a web interface at http://localhost:5173 and allow you to interact with the MCP tools for testing.\r\n\r\n## Available tools\r\n\r\n```\r\n\r\ngithub.com/mrexodia/user-feedback-mcp\r\nuser_feedback\r\n\r\n{\r\n \"project_directory\": \"C:/MCP/user-feedback-mcp\",\r\n \"summary\": \"I've implemented the changes you requested.\"\r\n}\r\n\r\n\r\n```","English","tag","en-US",{"_29":41,"_33":45,"_38":46},{"_31":42,"_33":43,"_35":44},"Servidor MCP simple que permite un flujo de trabajo con intervención humana en herramientas como Cline y Cursor. Esto resulta especialmente útil para desarrollar aplicaciones de escritorio que requieren interacciones complejas del usuario para realizar pruebas.","Comentarios de los usuarios","# Comentarios de los usuarios de MCP\n\n[Servidor MCP](https://modelcontextprotocol.io/introduction) simple que permite un flujo de trabajo con intervención humana en herramientas como [Cline](https://cline.bot) y [Cursor](https://www.cursor.com) . Esto resulta especialmente útil para desarrollar aplicaciones de escritorio que requieren interacciones complejas del usuario para su prueba.\n\n![Captura de pantalla que muestra la interfaz de usuario de comentarios](https://github.com/mrexodia/user-feedback-mcp/blob/main/.github/feedback-ui.png?raw=true)\n\n## Ingeniería rápida\n\nPara obtener los mejores resultados, agregue lo siguiente a su mensaje personalizado:\n\n> Antes de completar la tarea, utilice la herramienta MCP user\\_feedback para solicitarle comentarios al usuario.\n\nEsto garantizará que Cline utilice este servidor MCP para solicitar comentarios del usuario antes de marcar la tarea como completada.\n\n## `.user-feedback.json`\n\nAl hacer clic en *Guardar configuración,* se crea un archivo `.user-feedback.json` en el directorio del proyecto que se ve así:\n\n```json\n{\r\n \"command\": \"npm run dev\",\r\n \"execute_automatically\": false\r\n}\n```\n\nEsta configuración se cargará al iniciar y, si `execute_automatically` está habilitada, el `command` se ejecutará al instante (no tendrá que hacer clic en *\"Ejecutar\"* manualmente). Para comandos de varios pasos, debería usar algo como [\"Task\"](https://taskfile.dev) .\n\n## Instalación (Cline)\n\nPara instalar el servidor MCP en Cline, siga estos pasos (ver captura de pantalla):\n\n![Captura de pantalla que muestra los pasos de instalación](https://github.com/mrexodia/user-feedback-mcp/blob/main/.github/cline-installation.png?raw=true)\n\n1. Instalar [uv](https://github.com/astral-sh/uv) globalmente:\n * Windows: `pip install uv`\n * Linux/Mac: `curl -LsSf https://astral.sh/uv/install.sh | sh`\n2. Clonar este repositorio, para este ejemplo `C:\\MCP\\user-feedback-mcp` .\n3. Navegue hasta la configuración *de servidores Cline MCP* (ver captura de pantalla).\n4. Haga clic en la pestaña *Instalado* .\n5. Haga clic en *Configurar servidores MCP* , lo que abrirá `cline_mcp_settings.json` .\n6. Agregue el servidor `user-feedback-mcp` :\n\n```json\n{\r\n \"mcpServers\": {\r\n \"github.com/mrexodia/user-feedback-mcp\": {\r\n \"command\": \"uv\",\r\n \"args\": [\r\n \"--directory\",\r\n \"c:\\\\MCP\\\\user-feedback-mcp\",\r\n \"run\",\r\n \"server.py\"\r\n ],\r\n \"timeout\": 600,\r\n \"autoApprove\": [\r\n \"user_feedback\"\r\n ]\r\n }\r\n }\r\n}\r\n\n```\n\n## Desarrollo\n\n```sh\nuv run fastmcp dev server.py\n```\n\nEsto abrirá una interfaz web en y le permitirá interactuar con las herramientas MCP para realizar pruebas.\n\n## Herramientas disponibles\n\n```\n\r\ngithub.com/mrexodia/user-feedback-mcp\r\nuser_feedback\r\n\r\n{\r\n \"project_directory\": \"C:/MCP/user-feedback-mcp\",\r\n \"summary\": \"I've implemented the changes you requested.\"\r\n}\r\n\r\n\n```","Spanish","es-ES",{"_29":48,"_33":52,"_38":53},{"_31":49,"_33":50,"_35":51},"ClineやCursorなどのツールで人間参加型ワークフローを実現するシンプルなMCPサーバー。これは、複雑なユーザーインタラクションのテストを必要とするデスクトップアプリケーションの開発に特に役立ちます。","ユーザーフィードバック","# ユーザーフィードバック MCP\n\n[Cline](https://cline.bot)や[Cursor](https://www.cursor.com)などのツールで人間参加型ワークフローを実現するシンプルな[MCPサーバー](https://modelcontextprotocol.io/introduction)。これは、複雑なユーザーインタラクションのテストを必要とするデスクトップアプリケーションの開発に特に役立ちます。\n\n![フィードバック UI を示すスクリーンショット](https://github.com/mrexodia/user-feedback-mcp/blob/main/.github/feedback-ui.png?raw=true)\n\n## プロンプトエンジニアリング\n\n最良の結果を得るには、カスタムプロンプトに次の内容を追加します。\n\n> タスクを完了する前に、user\\_feedback MCP ツールを使用してユーザーにフィードバックを求めます。\n\nこれにより、Cline はタスクを完了としてマークする前に、この MCP サーバーを使用してユーザーからのフィードバックを要求するようになります。\n\n## `.user-feedback.json`\n\n\\*「構成を保存」\\*をクリックすると、プロジェクトディレクトリに次のような`.user-feedback.json`ファイルが作成されます。\n\n```json\n{\r\n \"command\": \"npm run dev\",\r\n \"execute_automatically\": false\r\n}\n```\n\nこの設定は起動時に読み込まれ、 `execute_automatically`有効になっている場合は`command`が即座に実行されます（手動で\\*「実行」を\\*クリックする必要はありません）。複数のステップを実行するコマンドの場合は、 [Task](https://taskfile.dev)のようなコマンドを使用してください。\n\n## インスタレーション（クライン）\n\nCline に MCP サーバーをインストールするには、次の手順に従います (スクリーンショットを参照)。\n\n![インストール手順を示すスクリーンショット](https://github.com/mrexodia/user-feedback-mcp/blob/main/.github/cline-installation.png?raw=true)\n\n1. [uvを](https://github.com/astral-sh/uv)グローバルにインストールします。\n * Windows: `pip install uv`\n * Linux/Mac: `curl -LsSf https://astral.sh/uv/install.sh | sh`\n2. このリポジトリをクローンします (この例では`C:\\MCP\\user-feedback-mcp` )。\n3. Cline *MCP サーバーの*構成に移動します (スクリーンショットを参照)。\n4. \\*「インストール済み」\\*タブをクリックします。\n5. \\*「MCP サーバーの構成」\\*をクリックすると、 `cline_mcp_settings.json`が開きます。\n6. `user-feedback-mcp`サーバーを追加します。\n\n```json\n{\r\n \"mcpServers\": {\r\n \"github.com/mrexodia/user-feedback-mcp\": {\r\n \"command\": \"uv\",\r\n \"args\": [\r\n \"--directory\",\r\n \"c:\\\\MCP\\\\user-feedback-mcp\",\r\n \"run\",\r\n \"server.py\"\r\n ],\r\n \"timeout\": 600,\r\n \"autoApprove\": [\r\n \"user_feedback\"\r\n ]\r\n }\r\n }\r\n}\r\n\n```\n\n## 発達\n\n```sh\nuv run fastmcp dev server.py\n```\n\nこれにより[、http://localhost:5173](http://localhost:5173)で Web インターフェイスが開き、テスト用の MCP ツールを操作できるようになります。\n\n## 利用可能なツール\n\n```\n\r\ngithub.com/mrexodia/user-feedback-mcp\r\nuser_feedback\r\n\r\n{\r\n \"project_directory\": \"C:/MCP/user-feedback-mcp\",\r\n \"summary\": \"I've implemented the changes you requested.\"\r\n}\r\n\r\n\n```","Japanese","ja-JP",{"_29":55,"_33":59,"_38":60},{"_31":56,"_33":57,"_35":58},"Cline 및 Cursor와 같은 도구에서 휴먼 인더 루프(Human-in-the-Loop) 워크플로를 구현하는 간단한 MCP 서버입니다. 특히 복잡한 사용자 상호작용을 테스트해야 하는 데스크톱 애플리케이션 개발에 유용합니다.","사용자 피드백","# 사용자 피드백 MCP\n\n[Cline](https://cline.bot) 및 [Cursor](https://www.cursor.com) 와 같은 도구에서 휴먼 인더 루프(Human-in-the-Loop) 워크플로를 구현하는 간단한 [MCP 서버입니다](https://modelcontextprotocol.io/introduction) . 특히 복잡한 사용자 상호작용을 테스트해야 하는 데스크톱 애플리케이션 개발에 유용합니다.\n\n![피드백 UI를 보여주는 스크린샷](https://github.com/mrexodia/user-feedback-mcp/blob/main/.github/feedback-ui.png?raw=true)\n\n## 신속한 엔지니어링\n\n최상의 결과를 얻으려면 사용자 지정 프롬프트에 다음을 추가하세요.\n\n> 작업을 완료하기 전에 user\\_feedback MCP 도구를 사용하여 사용자에게 피드백을 요청하세요.\n\n이렇게 하면 클라인이 작업을 완료로 표시하기 전에 이 MCP 서버를 사용하여 사용자 피드백을 요청할 수 있습니다.\n\n## `.user-feedback.json`\n\n*구성 저장을* 클릭하면 프로젝트 디렉토리에 다음과 같은 `.user-feedback.json` 파일이 생성됩니다.\n\n지엑스피1\n\n이 구성은 시작 시 로드되며, `execute_automatically` 활성화되어 있으면 `command` 즉시 실행됩니다( *실행을* 수동으로 클릭할 필요가 없습니다). 여러 단계로 구성된 명령의 경우 [Task](https://taskfile.dev) 와 같은 것을 사용해야 합니다.\n\n## 설치(클라인)\n\n클라인에 MCP 서버를 설치하려면 다음 단계를 따르세요(스크린샷 참조):\n\n![설치 단계를 보여주는 스크린샷](https://github.com/mrexodia/user-feedback-mcp/blob/main/.github/cline-installation.png?raw=true)\n\n1. [uv를](https://github.com/astral-sh/uv) 전역적으로 설치합니다.\n * 윈도우: `pip install uv`\n * Linux/Mac: `curl -LsSf https://astral.sh/uv/install.sh | sh`\n2. 이 저장소를 복제합니다(예 `C:\\MCP\\user-feedback-mcp` .\n3. Cline *MCP 서버* 구성으로 이동합니다(스크린샷 참조).\n4. *설치됨* 탭을 클릭합니다.\n5. *MCP 서버 구성을* 클릭하면 `cline_mcp_settings.json` 이 열립니다.\n6. `user-feedback-mcp` 서버를 추가합니다.\n\n```json\n{\r\n \"mcpServers\": {\r\n \"github.com/mrexodia/user-feedback-mcp\": {\r\n \"command\": \"uv\",\r\n \"args\": [\r\n \"--directory\",\r\n \"c:\\\\MCP\\\\user-feedback-mcp\",\r\n \"run\",\r\n \"server.py\"\r\n ],\r\n \"timeout\": 600,\r\n \"autoApprove\": [\r\n \"user_feedback\"\r\n ]\r\n }\r\n }\r\n}\r\n\n```\n\n## 개발\n\n```sh\nuv run fastmcp dev server.py\n```\n\n이렇게 하면 에서 웹 인터페이스가 열리고 테스트를 위해 MCP 도구와 상호 작용할 수 있습니다.\n\n## 사용 가능한 도구\n\n```\n\r\ngithub.com/mrexodia/user-feedback-mcp\r\nuser_feedback\r\n\r\n{\r\n \"project_directory\": \"C:/MCP/user-feedback-mcp\",\r\n \"summary\": \"I've implemented the changes you requested.\"\r\n}\r\n\r\n\n```","Korean","ko-KR",{"_29":62,"_33":66,"_38":67},{"_31":63,"_33":64,"_35":65},"简单的 MCP 服务器，可在 Cline 和 Cursor 等工具中实现人机交互工作流。这对于开发需要测试复杂用户交互的桌面应用程序尤其有用。","用户反馈","# 用户反馈 MCP\n\n简单的[MCP 服务器](https://modelcontextprotocol.io/introduction)，可在[Cline](https://cline.bot)和[Cursor](https://www.cursor.com)等工具中实现人机交互工作流。这对于开发需要进行复杂用户交互测试的桌面应用程序尤其有用。\n\n![显示反馈 UI 的屏幕截图](https://github.com/mrexodia/user-feedback-mcp/blob/main/.github/feedback-ui.png?raw=true)\n\n## 快速工程\n\n为了获得最佳效果，请将以下内容添加到您的自定义提示中：\n\n> 在完成任务之前，使用 user\\_feedback MCP 工具向用户征求反馈。\n\n这将确保 Cline 在将任务标记为完成之前使用此 MCP 服务器来请求用户反馈。\n\n## `.user-feedback.json`\n\n点击\\*“保存配置”\\*会在您的项目目录中创建一个`.user-feedback.json`文件，如下所示：\n\n```json\n{\r\n \"command\": \"npm run dev\",\r\n \"execute_automatically\": false\r\n}\n```\n\n此配置将在启动时加载，如果启用了`execute_automatically` ，您的`command`将立即执行（无需手动点击\\*“运行\\*”）。对于多步骤命令，您应该使用类似[Task 的](https://taskfile.dev)命令。\n\n## 装置（克莱恩）\n\n要在 Cline 中安装 MCP 服务器，请按照以下步骤操作（见屏幕截图）：\n\n![显示安装步骤的屏幕截图](https://github.com/mrexodia/user-feedback-mcp/blob/main/.github/cline-installation.png?raw=true)\n\n1. 全局安装[uv](https://github.com/astral-sh/uv) ：\n * Windows： `pip install uv`\n * Linux/Mac： `curl -LsSf https://astral.sh/uv/install.sh | sh`\n2. 克隆此存储库，本例中为`C:\\MCP\\user-feedback-mcp` 。\n3. 导航到 Cline *MCP 服务器*配置（见屏幕截图）。\n4. 单击\\*“已安装\\*”选项卡。\n5. 单击*配置 MCP 服务器*，将打开`cline_mcp_settings.json` 。\n6. 添加`user-feedback-mcp`服务器：\n\n```json\n{\r\n \"mcpServers\": {\r\n \"github.com/mrexodia/user-feedback-mcp\": {\r\n \"command\": \"uv\",\r\n \"args\": [\r\n \"--directory\",\r\n \"c:\\\\MCP\\\\user-feedback-mcp\",\r\n \"run\",\r\n \"server.py\"\r\n ],\r\n \"timeout\": 600,\r\n \"autoApprove\": [\r\n \"user_feedback\"\r\n ]\r\n }\r\n }\r\n}\r\n\n```\n\n## 发展\n\n```sh\nuv run fastmcp dev server.py\n```\n\n这将在打开一个 Web 界面并允许您与 MCP 工具进行交互以进行测试。\n\n## 可用工具\n\n```\n\r\ngithub.com/mrexodia/user-feedback-mcp\r\nuser_feedback\r\n\r\n{\r\n \"project_directory\": \"C:/MCP/user-feedback-mcp\",\r\n \"summary\": \"I've implemented the changes you 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MCP directory API