[{"_1":2,"_315":-5,"_316":-5},"loaderData",{"_3":4,"_32":33,"_34":35,"_259":260},"root",{"_5":6,"_17":18},"toasts",[7,14],{"_8":9,"_10":11,"_12":13},"uid","01984a69-86aa-77b2-80b2-9847a591b2c2","title","You need to sign in to access this page","type","error",{"_8":15,"_10":16,"_12":13},"01984a69-895a-7324-8699-00582acba6a9","Tool not found","visitor",{"_19":20,"_21":22},"viewportWidth",1280,"visitorSession",{"_23":24,"_26":27,"_28":-5,"_29":30,"_31":-5},"attributes",[25],"bot","id",9821443,"membership","referenceId","019843b4-2323-76ea-bef4-84db4bc95c8a","userAccount","routes/_public/_layout",{},"routes/_public/mcp/servers/~namespace/~slug/_pages/_layout",{"_36":37,"_78":-5,"_79":38,"_39":80,"_178":179,"_258":131},"availableLocales",[38,50,57,64,71],{"_39":40,"_43":47,"_48":49},"mcpServer",{"_41":42,"_43":44,"_45":46},"description","A tool that helps easily register Anthropic's Model Context Protocol (MCP) in Claude Desktop and Cursor, providing RAG functionality, Dify integration, and web search capabilities.","name","Quick-start Auto MCP","readme","# Quick-start Auto MCP : All in one Claude Desktop and Cursor\n\n[English](README.md) | [한국어](README_KR.md)\n\n## Introduction\n\n**Quick-start Auto MCP** is a tool that helps you easily and quickly register Anthropic's Model Context Protocol (MCP) in Claude Desktop and Cursor.\n\n**Key advantages:**\n1. **Quick Setup**: Add MCP functionality to Claude Desktop and Cursor simply by running a tool and copying/pasting the generated JSON file.\n2. **Various Tools Provided**: We continuously update useful MCP tools. Stay up to date with your personalized toolkit by starring and following us. :)\n\n## Table of Contents\n\n- [Features](#features)\n- [Project Structure](#project-structure)\n- [Requirements](#requirements)\n- [Installation](#installation)\n- [Configuration](#configuration)\n- [Usage](#usage)\n- [Troubleshooting](#troubleshooting)\n- [License](#license)\n- [Contributing](#contributing)\n- [Contact](#contact)\n- [Author](#author)\n\n## Features\n\n- **RAG (Retrieval Augmented Generation)** - Keyword, semantic, and hybrid search functionality for PDF documents\n- **Dify External Knowledge API** - Document search functionality via Dify's external knowledge API\n- **Dify Workflow** - Execute and retrieve results from Dify Workflow\n- **Web Search** - Real-time web search using Tavily API\n- **Automatic JSON Generation** - Automatically generate MCP JSON files needed for Claude Desktop and Cursor\n\n## Project Structure\n\n```\n.\n├── case1 # RAG example\n├── case2 # Dify External Knowledge API example\n├── case3 # Dify Workflow example\n├── case4 # Web Search example\n├── data # Example data files\n├── docs # Documentation folder\n│ ├── case1.md # case1 description 🚨 Includes tips for optimized tool invocation\n│ ├── case2.md # case2 description\n│ ├── case3.md # case3 description\n│ ├── case4.md # case4 description\n│ └── installation.md # Installation guide\n├── .env.example # .env example format\n├── pyproject.toml # Project settings\n├── requirements.txt # Required packages list\n└── uv.lock # uv.lock\n```\n\n## Requirements\n\n- Python >= 3.11\n- Claude Desktop or Cursor (MCP supporting version)\n- uv (recommended) or pip\n\n## Installation\n\n### 1. Clone the repository\n\n```bash\ngit clone https://github.com/teddynote-lab/mcp.git\ncd mcp\n```\n\n### 2. Set up virtual environment\n\n#### Using uv (recommended)\n```bash\n# macOS/Linux\nuv venv\nuv pip install -r requirements.txt\n```\n\n```bash\n# Windows\nuv venv\nuv pip install -r requirements_windows.txt\n```\n\n#### Using pip\n```bash\npython -m venv .venv\n\n# Windows\n.venv\\Scripts\\activate\npip install -r requirements_windows.txt\n\n# macOS/Linux\nsource .venv/bin/activate\n\npip install -r requirements.txt\n```\n\n### 3. Preparing the PDF File\n\nPlese prepare a PDF file required for RAG in the `./data` directory.\n\n## Configuration\n\nIn order to execute each case, a `.env` file is required.\nPlease specify the necessary environment variables in the `.env.example` file located in the root directory, and rename it to `.env`.\n\n### sites for configuring required environment variables for each case\n- https://platform.openai.com/api-keys\n- https://dify.ai/\n- https://app.tavily.com/home\n\n## Usage\n\n### 1. Generate JSON File\n\nRun the following command in each case directory to generate the necessary JSON file:\n\n```bash\n# Activate virtual environment\n\n# Windows\n.venv\\Scripts\\activate\n\n# macOS/Linux\nsource .venv/bin/activate\n\n# Navigate to example directory\ncd case1\n\n# Generate JSON file\npython auto_mcp_json.py\n```\n\n### 2. Register MCP in Claude Desktop/Cursor\n\n1. Launch Claude Desktop or Cursor\n2. Open MCP settings menu\n3. Copy and paste the generated JSON content\n4. Save and `restart`\n\n> **Note**: When you run Claude Desktop or Cursor, the MCP server will automatically run with it. When you close the software, the MCP server will also terminate.\n\n## Troubleshooting\n\nCommon issues and solutions:\n\n- **MCP Server Connection Failure**: Check if the service is running properly and if there are no port conflicts. In particular, when applying case2, you must also run `dify_ek_server.py`.\n- **API Key Errors**: Verify that environment variables are set correctly.\n- **Virtual Environment Issues**: Ensure Python version is 3.11 or higher.\n\n## License\n\n[MIT LICENSE](LICENSE.md)\n\n## Contributing\n\nContributions are always welcome! Please participate in the project through issue registration or pull requests. :)\n\n## Contact\n\nIf you have questions or need help, please register an issue or contact:\ndev@brain-crew.com\n\n## Author\n[Hantaek Lim](https://github.com/LHANTAEK)","English","tag","en-US",{"_39":51,"_43":55,"_48":56},{"_41":52,"_43":53,"_45":54},"Una herramienta que ayuda a registrar fácilmente el Protocolo de Contexto de Modelo (MCP) de Anthropic en Claude Desktop y Cursor, proporcionando funcionalidad RAG, integración con Dify y capacidades de búsqueda web.","Inicio rápido de Auto MCP","# Inicio rápido Auto MCP: Todo en uno Claude Desktop y Cursor\n\n[Inglés](README.md) | [Coreano](README_KR.md)\n\n## Introducción\n\n**Quick-start Auto MCP** es una herramienta que le ayuda a registrar de manera fácil y rápida el Protocolo de contexto de modelo (MCP) de Anthropic en Claude Desktop y Cursor.\n\n**Ventajas clave:**\n\n1. **Configuración rápida** : agregue la funcionalidad MCP a Claude Desktop y Cursor simplemente ejecutando una herramienta y copiando/pegando el archivo JSON generado.\n2. **Diversas herramientas disponibles** : Actualizamos constantemente herramientas útiles de MCP. Manténgase al día con su kit de herramientas personalizado marcándonos con una estrella y siguiéndonos. :)\n\n## Tabla de contenido\n\n* [Características](#features)\n* [Estructura del proyecto](#project-structure)\n* [Requisitos](#requirements)\n* [Instalación](#installation)\n* [Configuración](#configuration)\n* [Uso](#usage)\n* [Solución de problemas](#troubleshooting)\n* [Licencia](#license)\n* [Contribuyendo](#contributing)\n* [Contacto](#contact)\n* [Autor](#author)\n\n## Características\n\n* **RAG (Recuperación de Generación Aumentada)** : funcionalidad de búsqueda por palabras clave, semántica e híbrida para documentos PDF\n* **API de conocimiento externo de Dify** : funcionalidad de búsqueda de documentos a través de la API de conocimiento externo de Dify\n* **Flujo de trabajo de Dify** : ejecutar y recuperar resultados de Dify Workflow\n* **Búsqueda web** : búsqueda web en tiempo real mediante la API de Tavily\n* **Generación automática de JSON** : genere automáticamente los archivos JSON de MCP necesarios para Claude Desktop y Cursor\n\n## Estructura del proyecto\n\n```\n.\n├── case1 # RAG example\n├── case2 # Dify External Knowledge API example\n├── case3 # Dify Workflow example\n├── case4 # Web Search example\n├── data # Example data files\n├── docs # Documentation folder\n│ ├── case1.md # case1 description 🚨 Includes tips for optimized tool invocation\n│ ├── case2.md # case2 description\n│ ├── case3.md # case3 description\n│ ├── case4.md # case4 description\n│ └── installation.md # Installation guide\n├── .env.example # .env example format\n├── pyproject.toml # Project settings\n├── requirements.txt # Required packages list\n└── uv.lock # uv.lock\n```\n\n## Requisitos\n\n* Python >= 3.11\n* Claude Desktop o Cursor (versión compatible con MCP)\n* uv (recomendado) o pip\n\n## Instalación\n\n### 1. Clonar el repositorio\n\n```bash\ngit clone https://github.com/teddynote-lab/mcp.git\ncd mcp\n```\n\n### 2. Configurar el entorno virtual\n\n#### Uso de uv (recomendado)\n\n```bash\n# macOS/Linux\nuv venv\nuv pip install -r requirements.txt\n```\n\n```bash\n# Windows\nuv venv\nuv pip install -r requirements_windows.txt\n```\n\n#### Usando pip\n\n```bash\npython -m venv .venv\n\n# Windows\n.venv\\Scripts\\activate\npip install -r requirements_windows.txt\n\n# macOS/Linux\nsource .venv/bin/activate\n\npip install -r requirements.txt\n```\n\n### 3. Preparación del archivo PDF\n\nPrepare el archivo PDF necesario para RAG en el directorio `./data` .\n\n## Configuración\n\nPara ejecutar cada caso, se requiere un archivo `.env` . Especifique las variables de entorno necesarias en el archivo `.env.example` , ubicado en el directorio raíz, y renómbrelo como `.env` .\n\n### sitios para configurar las variables de entorno requeridas para cada caso\n\n* \n* \n* [https://app.tavily.com/inicio](https://app.tavily.com/home)\n\n## Uso\n\n### 1. Generar archivo JSON\n\nEjecute el siguiente comando en cada directorio de caso para generar el archivo JSON necesario:\n\n```bash\n# Activate virtual environment\n\n# Windows\n.venv\\Scripts\\activate\n\n# macOS/Linux\nsource .venv/bin/activate\n\n# Navigate to example directory\ncd case1\n\n# Generate JSON file\npython auto_mcp_json.py\n```\n\n### 2. Registrar MCP en Claude Desktop/Cursor\n\n1. Inicie Claude Desktop o Cursor\n2. Abrir el menú de configuración de MCP\n3. Copia y pega el contenido JSON generado\n4. Guardar y `restart`\n\n> **Nota** : Al ejecutar Claude Desktop o Cursor, el servidor MCP se ejecutará automáticamente. Al cerrar el software, el servidor MCP también se cerrará.\n\n## Solución de problemas\n\nProblemas comunes y soluciones:\n\n* **Fallo de conexión al servidor MCP** : Compruebe si el servicio funciona correctamente y si no hay conflictos de puertos. En particular, al aplicar el caso 2, también debe ejecutar `dify_ek_server.py` .\n* **Errores de clave API** : Verifique que las variables de entorno estén configuradas correctamente.\n* **Problemas del entorno virtual** : asegúrese de que la versión de Python sea 3.11 o superior.\n\n## Licencia\n\n[LICENCIA MIT](LICENSE.md)\n\n## Contribuyendo\n\n¡Las contribuciones siempre son bienvenidas! Por favor, participa en el proyecto mediante el registro de problemas o solicitudes de incorporación de cambios. :)\n\n## Contacto\n\nSi tiene preguntas o necesita ayuda, registre un problema o comuníquese con: \n\n## Autor\n\n[Hantaek Lim](https://github.com/LHANTAEK)","Spanish","es-ES",{"_39":58,"_43":62,"_48":63},{"_41":59,"_43":60,"_45":61},"Claude Desktop および Cursor に Anthropic の Model Context Protocol (MCP) を簡単に登録し、RAG 機能、Dify 統合、および Web 検索機能を提供するツールです。","クイックスタート自動MCP","# クイックスタートAuto MCP：オールインワンのClaudeデスクトップとカーソル\n\n[英語](README.md)|[韓国語](README_KR.md)\n\n## 導入\n\n**クイックスタート Auto MCP は、** Claude Desktop および Cursor に Anthropic の Model Context Protocol (MCP) を簡単かつ迅速に登録するのに役立つツールです。\n\n**主な利点:**\n\n1. **クイックセットアップ**: ツールを実行し、生成された JSON ファイルをコピー/貼り付けするだけで、Claude Desktop と Cursor に MCP 機能を追加できます。\n2. **様々なツールをご用意**：MCPの便利なツールを継続的に更新しています。スターを付けて��ォローして、あなただけのツールキットの最新情報を入手しましょう。 :)\n\n## 目次\n\n* [特徴](#features)\n* [プロジェクト構造](#project-structure)\n* [要件](#requirements)\n* [インストール](#installation)\n* [構成](#configuration)\n* [使用法](#usage)\n* [トラブルシューティング](#troubleshooting)\n* [ライセンス](#license)\n* [貢献](#contributing)\n* [接触](#contact)\n* [著者](#author)\n\n## 特徴\n\n* **RAG (Retrieval Augmented Generation)** - PDF ドキュメントのキーワード、セマンティック、ハイブリッド検索機能\n* **Dify 外部ナレッジ API** - Dify の外部ナレッジ API を介したドキュメント検索機能\n* **Dify Workflow** - Dify Workflow を実行して結果を取得する\n* **Web検索**- Tavily APIを使用したリアルタイムWeb検索\n* **自動JSON生成**- Claude DesktopとCursorに必要なMCP JSONファイルを自動生成します\n\n## プロジェクト構造\n\n```\n.\n├── case1 # RAG example\n├── case2 # Dify External Knowledge API example\n├── case3 # Dify Workflow example\n├── case4 # Web Search example\n├── data # Example data files\n├── docs # Documentation folder\n│ ├── case1.md # case1 description 🚨 Includes tips for optimized tool invocation\n│ ├── case2.md # case2 description\n│ ├── case3.md # case3 description\n│ ├── case4.md # case4 description\n│ └── installation.md # Installation guide\n├── .env.example # .env example format\n├── pyproject.toml # Project settings\n├── requirements.txt # Required packages list\n└── uv.lock # uv.lock\n```\n\n## 要件\n\n* Python >= 3.11\n* Claude Desktop または Cursor (MCP 対応バージョン)\n* uv（推奨）またはpip\n\n## インストール\n\n### 1. リポジトリをクローンする\n\n```bash\ngit clone https://github.com/teddynote-lab/mcp.git\ncd mcp\n```\n\n### 2. 仮想環境をセットアップする\n\n#### uvの使用（推奨）\n\n```bash\n# macOS/Linux\nuv venv\nuv pip install -r requirements.txt\n```\n\n```bash\n# Windows\nuv venv\nuv pip install -r requirements_windows.txt\n```\n\n#### pipの使用\n\n```bash\npython -m venv .venv\n\n# Windows\n.venv\\Scripts\\activate\npip install -r requirements_windows.txt\n\n# macOS/Linux\nsource .venv/bin/activate\n\npip install -r requirements.txt\n```\n\n### 3. PDFファイルの準備\n\nRAG に必要な PDF ファイルを`./data`ディレクトリに用意してください。\n\n## 構成\n\n各ケースを実行するには、 `.env`ファイルが必要です。ルートディレクトリにある`.env.example`ファイルに必要な環境変数を指定し、ファイル名を`.env`に変更してください。\n\n### 各ケースに必要な環境変数を設定するためのサイト\n\n* \n* \n* \n\n## 使用法\n\n### 1. JSONファイルを生成する\n\n必要な JSON ファイルを生成するには、各ケースディレクトリで次のコマンドを実行します。\n\n```bash\n# Activate virtual environment\n\n# Windows\n.venv\\Scripts\\activate\n\n# macOS/Linux\nsource .venv/bin/activate\n\n# Navigate to example directory\ncd case1\n\n# Generate JSON file\npython auto_mcp_json.py\n```\n\n### 2. Claude Desktop/CursorにMCPを登録する\n\n1. Claudeデスクトップまたはカーソルを起動する\n2. MCP設定メニューを開く\n3. 生成されたJSONコンテンツをコピーして貼り付けます\n4. 保存して`restart`\n\n> **注**：Claude DesktopまたはCursorを実行すると、MCPサーバーも自動的に起動します。ソフトウェアを終了すると、MCPサーバーも終了します。\n\n## トラブルシューティング\n\nよくある問題と解決策:\n\n* **MCPサーバー接続失敗**：サービスが正常に動作しているか、ポートの競合がないか確認してください。特に、case2を適用する場合は、 `dify_ek_server.py`も実行する必要があります。\n* **API キーエラー**: 環境変数が正しく設定されていることを確認してください。\n* **仮想環境の問題**: Python バージョンが 3.11 以上であることを確認してください。\n\n## ライセンス\n\n[MITライセンス](LICENSE.md)\n\n## 貢献\n\n貢献はいつでも歓迎です！課題登録やプルリクエストを通じてプロジェクトにご参加ください。 :)\n\n## 接触\n\nご質問やご支援が必要な場合は、問題を登録するか、 [dev@](mailto:dev@brain-crew.com) brain-crew.com までご連絡ください。\n\n## 著者\n\n[ハンテク・イム](https://github.com/LHANTAEK)","Japanese","ja-JP",{"_39":65,"_43":69,"_48":70},{"_41":66,"_43":67,"_45":68},"Claude Desktop과 Cursor에서 Anthropic의 Model Context Protocol(MCP)을 쉽게 등록하고 RAG 기능, Dify 통합, 웹 검색 기능을 제공하는 도구입니다.","빠른 시작 자동 MCP","# 빠른 시작 자동 MCP: Claude 데스크탑 및 커서 일체형\n\n[영어](README.md) | [한국어](README_KR.md)\n\n## 소개\n\n**Quick-start Auto MCP는** Claude Desktop과 Cursor에서 Anthropic의 Model Context Protocol(MCP)을 쉽고 빠르게 등록하는 데 도움이 되는 도구입니다.\n\n**주요 장점:**\n\n1. **빠른 설정** : 도구를 실행하고 생성된 JSON 파일을 복사/붙여넣기만 하면 Claude Desktop과 Cursor에 MCP 기능을 추가할 수 있습니다.\n2. **다양한 도구 제공** : 유용한 MCP 도구가 지속적으로 업데이트됩니다. 저희를 팔로우하고 스타를 눌러 나만의 도구 키트를 최신 상태로 유지하세요. :)\n\n## 목차\n\n* [특징](#features)\n* [프로젝트 구조](#project-structure)\n* [요구 사항](#requirements)\n* [설치](#installation)\n* [구성](#configuration)\n* [용법](#usage)\n* [문제 해결](#troubleshooting)\n* [특허](#license)\n* [기여하다](#contributing)\n* [연락하다](#contact)\n* [작가](#author)\n\n## 특징\n\n* **RAG(Retrieval Augmented Generation)** - PDF 문서에 대한 키워드, 의미론적 검색 및 하이브리드 검색 기능\n* **Dify 외부 지식 API** - Dify의 외부 지식 API를 통한 문서 검색 기능\n* **Dify Workflow** - Dify Workflow에서 실행 및 결과 검색\n* **웹 검색** - Tavily API를 사용한 실시간 웹 검색\n* **자동 JSON 생성** - Claude Desktop 및 Cursor에 필요한 MCP JSON 파일을 자동으로 생성합니다.\n\n## 프로젝트 구조\n\n지엑스피1\n\n## 요구 사항\n\n* 파이썬 >= 3.11\n* Claude Desktop 또는 Cursor(MCP 지원 버전)\n* uv(권장) 또는 pip\n\n## 설치\n\n### 1. 저장소를 복제합니다.\n\n```bash\ngit clone https://github.com/teddynote-lab/mcp.git\ncd mcp\n```\n\n### 2. 가상 환경 설정\n\n#### uv 사용(권장)\n\n```bash\n# macOS/Linux\nuv venv\nuv pip install -r requirements.txt\n```\n\n```bash\n# Windows\nuv venv\nuv pip install -r requirements_windows.txt\n```\n\n#### pip 사용하기\n\n```bash\npython -m venv .venv\n\n# Windows\n.venv\\Scripts\\activate\npip install -r requirements_windows.txt\n\n# macOS/Linux\nsource .venv/bin/activate\n\npip install -r requirements.txt\n```\n\n### 3. PDF 파일 준비\n\nRAG에 필요한 PDF 파일을 `./data` 디렉토리에 준비해주세요.\n\n## 구성\n\n각 케이스를 실행하려면 `.env` 파일이 필요합니다. 루트 디렉터리에 있는 `.env.example` 파일에 필요한 환경 변수를 지정하고 파일 이름을 `.env` 로 변경하세요.\n\n### 각 사례에 필요한 환경 변수를 구성하기 위한 사이트\n\n* \n* \n* \n\n## 용법\n\n### 1. JSON 파일 생성\n\n각 케이스 디렉토리에서 다음 명령을 실행하여 필요한 JSON 파일을 생성합니다.\n\n```bash\n# Activate virtual environment\n\n# Windows\n.venv\\Scripts\\activate\n\n# macOS/Linux\nsource .venv/bin/activate\n\n# Navigate to example directory\ncd case1\n\n# Generate JSON file\npython auto_mcp_json.py\n```\n\n### 2. Claude Desktop/Cursor에 MCP 등록\n\n1. Claude Desktop 또는 Cursor 실행\n2. MCP 설정 메뉴 열기\n3. 생성된 JSON 콘텐츠를 복사하여 붙여넣습니다.\n4. 저장하고 `restart`\n\n> **참고** : Claude Desktop 또는 Cursor를 실행하면 MCP 서버도 자동으로 실행됩니다. 소프트웨어를 종료하면 MCP 서버도 종료됩니다.\n\n## 문제 해결\n\n일반적인 문제 및 해결 방법:\n\n* **MCP 서버 연결 실패** : 서비스가 정상적으로 실행되고 포트 충돌이 없는지 확인하세요. 특히 case2를 적용할 때는 `dify_ek_server.py` 도 함께 실행해야 합니다.\n* **API 키 오류** : 환경 변수가 올바르게 설정되었는지 확인하세요.\n* **가상 환경 문제** : Python 버전이 3.11 이상인지 확인하세요.\n\n## 특허\n\n[MIT 라이센스](LICENSE.md)\n\n## 기여하다\n\n여러분의 참여는 언제나 환영합니다! 이슈 등록이나 풀 리퀘스트를 통해 프로젝트에 참여해 주세요. :)\n\n## 연락하다\n\n질문이 있거나 도움이 필요하면 문제를 등록하거나 으로 문의하세요.\n\n## 작가\n\n[임한택](https://github.com/LHANTAEK)","Korean","ko-KR",{"_39":72,"_43":76,"_48":77},{"_41":73,"_43":74,"_45":75},"该工具可帮助在 Claude Desktop 和 Cursor 中轻松注册 Anthropic 的模型上下文协议 (MCP)，提供 RAG 功能、Dify 集成和网络搜索功能。","快速启动自动 MCP","# 快速启动自动 MCP：一体化 Claude 桌面和光标\n\n[English](README.md) |[韩语](README_KR.md)\n\n## 介绍\n\n**快速启动自动 MCP**是一种工具，可帮助您在 Claude Desktop 和 Cursor 中轻松快速地注册 Anthropic 的模型上下文协议 (MCP)。\n\n**主要优势：**\n\n1. **快速设置**：只需运行工具并复制/粘贴生成的 JSON 文件，即可将 MCP 功能添加到 Claude Desktop 和 Cursor。\n2. **提供各种工具**：我们持续更新实用的 MCP 工具。点赞并关注我们，即可随时获取您专属的工具包。:)\n\n## 目录\n\n* [特征](#features)\n* [项目结构](#project-structure)\n* [要求](#requirements)\n* [安装](#installation)\n* [配置](#configuration)\n* [用法](#usage)\n* [故障排除](#troubleshooting)\n* [执照](#license)\n* [贡献](#contributing)\n* [接触](#contact)\n* [作者](#author)\n\n## 特征\n\n* **RAG（检索增强生成）** ——PDF 文档的关键字、语义和混合搜索功能\n* **Dify 外部知识 API** - 通过 Dify 的外部知识 API 实现文档搜索功能\n* **Dify Workflow** - 执行并检索 Dify Workflow 的结果\n* **网络搜索**- 使用 Tavily API 进行实时网络搜索\n* **自动 JSON 生成**- 自动生成 Claude Desktop 和 Cursor 所需的 MCP JSON 文件\n\n## 项目结构\n\n```\n.\n├── case1 # RAG example\n├── case2 # Dify External Knowledge API example\n├── case3 # Dify Workflow example\n├── case4 # Web Search example\n├── data # Example data files\n├── docs # Documentation folder\n│ ├── case1.md # case1 description 🚨 Includes tips for optimized tool invocation\n│ ├── case2.md # case2 description\n│ ├── case3.md # case3 description\n│ ├── case4.md # case4 description\n│ └── installation.md # Installation guide\n├── .env.example # .env example format\n├── pyproject.toml # Project settings\n├── requirements.txt # Required packages list\n└── uv.lock # uv.lock\n```\n\n## 要求\n\n* Python >= 3.11\n* Claude Desktop 或 Cursor（MCP 支持版本）\n* uv（推荐）或 pip\n\n## 安装\n\n### 1. 克隆存储库\n\n```bash\ngit clone https://github.com/teddynote-lab/mcp.git\ncd mcp\n```\n\n### 2. 设置虚拟环境\n\n#### 使用 uv（推荐）\n\n```bash\n# macOS/Linux\nuv venv\nuv pip install -r requirements.txt\n```\n\n```bash\n# Windows\nuv venv\nuv pip install -r requirements_windows.txt\n```\n\n#### 使用 pip\n\n```bash\npython -m venv .venv\n\n# Windows\n.venv\\Scripts\\activate\npip install -r requirements_windows.txt\n\n# macOS/Linux\nsource .venv/bin/activate\n\npip install -r requirements.txt\n```\n\n### 3.准备PDF文件\n\n请在`./data`目录中准备 RAG 所需的 PDF 文件。\n\n## 配置\n\n为了执行每个案例，需要一个`.env`文件。请在根目录下的`.env.example`文件中指定必要的环境变量，并将其重命名为`.env` 。\n\n### 针对每种情况配置所需环境变量的站点\n\n* \n* \n* \n\n## 用法\n\n### 1.生成JSON文件\n\n在每个案例目录中运行以下命令来生成必要的 JSON 文件：\n\n```bash\n# Activate virtual environment\n\n# Windows\n.venv\\Scripts\\activate\n\n# macOS/Linux\nsource .venv/bin/activate\n\n# Navigate to example directory\ncd case1\n\n# Generate JSON file\npython auto_mcp_json.py\n```\n\n### 2. 在 Claude Desktop/Cursor 中注册 MCP\n\n1. 启动 Claude Desktop 或 Cursor\n2. 打开 MCP 设置菜单\n3. 复制并粘贴生成的 JSON 内容\n4. 保存并`restart`\n\n> **注意**：当您运行 Claude Desktop 或 Cursor 时，MCP 服务器将自动随之运行。当您关闭软件时，MCP 服务器也将终止。\n\n## 故障排除\n\n常见问题及解决方案：\n\n* **MCP 服务器连接失败**：请检查服务是否正常运行，以及是否存在端口冲突。特别需要注意的是，在应用 case2 时，还必须运行`dify_ek_server.py` 。\n* **API 密钥错误**：验证环境变量是否设置正确。\n* **虚拟环境问题**：确保 Python 版本为 3.11 或更高版本。\n\n## 执照\n\n[麻省理工学院许可证](LICENSE.md)\n\n## 贡献\n\n欢迎大家贡献代码！请通过注册问题或提交拉取请求来参与项目。:)\n\n## 接触\n\n如果您有疑问或需要帮助，请注册问题或联系： \n\n## 作者\n\n[林韩泽](https://github.com/LHANTAEK)","Chinese","zh-CN","githubUser","locale",{"_81":82,"_83":84,"_23":90,"_98":42,"_99":42,"_100":101,"_105":106,"_128":-5,"_26":129,"_130":131,"_132":133,"_43":44,"_157":119,"_158":-5,"_159":-5,"_160":-5,"_161":-5,"_162":163,"_168":-5,"_140":115,"_169":170,"_174":-5,"_8":175,"_176":177},"addedAt","2025-03-23T17:02:43.358358699Z","argumentsJsonSchema",{"_85":86,"_87":88,"_12":89},"properties",{},"required",[],"object",[91,92,93,94,95,96,97],"category:rag-systems","category:search","category:developer-tools","environment:network","hosting:local-only","language:python","license_grade:a","descriptionMarkdown","descriptionPlainText","githubProject",{"_45":102,"_103":104},"# Quick-start Auto MCP : All in one Claude Desktop and Cursor\n\n[English](README.md) | [한국어](README_KR.md)\n\n## Introduction\n\n**Quick-start Auto MCP** is a tool that helps you easily and quickly register Anthropic's Model Context Protocol (MCP) in Claude Desktop and Cursor.\n\n**Key advantages:**\n1. **Quick Setup**: Add MCP functionality to Claude Desktop and Cursor simply by running a tool and copying/pasting the generated JSON file.\n2. **Various Tools Provided**: We continuously update useful MCP tools. Stay up to date with your personalized toolkit by starring and following us. :)\n\n## Table of Contents\n\n- [Features](#features)\n- [Project Structure](#project-structure)\n- [Requirements](#requirements)\n- [Installation](#installation)\n- [Configuration](#configuration)\n- [Usage](#usage)\n- [Troubleshooting](#troubleshooting)\n- [License](#license)\n- [Contributing](#contributing)\n- [Contact](#contact)\n- [Author](#author)\n\n## Features\n\n- **RAG (Retrieval Augmented Generation)** - Keyword, semantic, and hybrid search functionality for PDF documents\n- **Dify External Knowledge API** - Document search functionality via Dify's external knowledge API\n- **Dify Workflow** - Execute and retrieve results from Dify Workflow\n- **Web Search** - Real-time web search using Tavily API\n- **Automatic JSON Generation** - Automatically generate MCP JSON files needed for Claude Desktop and Cursor\n\n## Project Structure\n\n```\n.\n├── case1 # RAG example\n├── case2 # Dify External Knowledge API example\n├── case3 # Dify Workflow example\n├── case4 # Web Search example\n├── data # Example data files\n├── docs # Documentation folder\n│ ├── case1.md # case1 description 🚨 Includes tips for optimized tool invocation\n│ ├── case2.md # case2 description\n│ ├── case3.md # case3 description\n│ ├── case4.md # case4 description\n│ └── installation.md # Installation guide\n├── .env.example # .env example format\n├── pyproject.toml # Project settings\n├── requirements.txt # Required packages list\n└── uv.lock # uv.lock\n```\n\n## Requirements\n\n- Python >= 3.11\n- Claude Desktop or Cursor (MCP supporting version)\n- uv (recommended) or pip\n\n## Installation\n\n### 1. Clone the repository\n\n```bash\ngit clone https://github.com/teddynote-lab/mcp.git\ncd mcp\n```\n\n### 2. Set up virtual environment\n\n#### Using uv (recommended)\n```bash\n# macOS/Linux\nuv venv\nuv pip install -r requirements.txt\n```\n\n```bash\n# Windows\nuv venv\nuv pip install -r requirements_windows.txt\n```\n\n#### Using pip\n```bash\npython -m venv .venv\n\n# Windows\n.venv\\Scripts\\activate\npip install -r requirements_windows.txt\n\n# macOS/Linux\nsource .venv/bin/activate\n\npip install -r requirements.txt\n```\n\n### 3. Preparing the PDF File\n\nPlese prepare a PDF file required for RAG in the `./data` directory.\n\n## Configuration\n\nIn order to execute each case, a `.env` file is required.\nPlease specify the necessary environment variables in the `.env.example` file located in the root directory, and rename it to `.env`.\n\n### sites for configuring required environment variables for each case\n- https://platform.openai.com/api-keys\n- https://dify.ai/\n- https://app.tavily.com/home\n\n## Usage\n\n### 1. Generate JSON File\n\nRun the following command in each case directory to generate the necessary JSON file:\n\n```bash\n# Activate virtual environment\n\n# Windows\n.venv\\Scripts\\activate\n\n# macOS/Linux\nsource .venv/bin/activate\n\n# Navigate to example directory\ncd case1\n\n# Generate JSON file\npython auto_mcp_json.py\n```\n\n### 2. Register MCP in Claude Desktop/Cursor\n\n1. Launch Claude Desktop or Cursor\n2. Open MCP settings menu\n3. Copy and paste the generated JSON content\n4. Save and `restart` (If you're using Windows, we recommend fully closing the process via Task Manager and then restarting the application.)\n\n> **Note**: When you run Claude Desktop or Cursor, the MCP server will automatically run with it. When you close the software, the MCP server will also terminate.\n\n## Troubleshooting\n\nCommon issues and solutions:\n\n- **MCP Server Connection Failure**: Check if the service is running properly and if there are no port conflicts. In particular, when applying case2, you must also run `dify_ek_server.py`.\n- **API Key Errors**: Verify that environment variables are set correctly.\n- **Virtual Environment Issues**: Ensure Python version is 3.11 or higher.\n\n## License\n\n[MIT LICENSE](LICENSE.md)\n\n## Contributing\n\nContributions are always welcome! Please participate in the project through issue registration or pull requests. :)\n\n## Contact\n\nIf you have questions or need help, please register an issue or contact:\ndev@brain-crew.com\n\n## Author\n[Hantaek Lim](https://github.com/LHANTAEK)","url","https://github.com/teddynote-lab/mcp-usecase","githubRepository",{"_107":108,"_109":110,"_111":112,"_113":114,"_43":115,"_116":117,"_121":122,"_123":124,"_126":127},"defaultBranch","main","fullName","teddynote-lab/mcp-usecase","githubTreeId",140283,"language","Python","mcp-usecase","owner",{"_118":119,"_8":120},"login","teddynote-lab","zBFF20Whte","recentStargazers",1,"spdxLicense",{"_43":125},"MIT License","stargazers",182,"glamaJson",3264,"inspectable",false,"integrations",[134,144,151],{"_135":136,"_41":142,"_8":143},"brand",{"_137":138,"_43":139,"_140":141},"logoSvgPath","M24 0v24H0V0h24ZM10.933 15.89H6.84v5.52h4.198v-.93H7.955v-1.503h2.77v-.93h-2.77v-1.224h2.978v-.934Zm2.146 0h-1.084v5.52h1.035v-3.6l2.226 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