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引言

快速启动自动MCP 是一个工具，帮助您轻松快速地在 Claude 桌面和光标中注册 Anthropic 的模型上下文协议（MCP）。

主要优势：

1. 快速设置：只需运行工具并复制粘贴生成的JSON文件，即可为Claude桌面和光标添加MCP功能。
2. 提供多种工具：我们持续更新有用的MCP工具。通过点名和关注我们，随时掌握您的个性化工具包。:)

目录

• 特色
• 项目结构
• 要求
• 安装
• 配置
• 使用情况
• 故障排除
• 许可证
• 贡献
• 联系方式
• 作家

特色

• RAG（检索增强生成） - PDF文档的关键词、语义和混合搜索功能
• Dify 外部知识 API - 通过 Dify 外部知识 API 实现文档搜索功能
• Dify 工作流程 - 执行并检索 Dify 工作流程的结果
• Web 搜索 - 使用 Tavily API 的实时网页搜索
• 自动 JSON 生成 - 自动生成 Claude Desktop 和光标所需的 MCP JSON 文件

项目结构

要求

• Python >= 3.11

Quick-start Auto MCP : All in one Claude Desktop and Cursor

English | 한국어

Introduction

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.

Key advantages:

1. Quick Setup: Add MCP functionality to Claude Desktop and Cursor simply by running a tool and copying/pasting the generated JSON file.
2. Various Tools Provided: We continuously update useful MCP tools. Stay up to date with your personalized toolkit by starring and following us. :)

Table of Contents

• Features
• Project Structure
• Requirements
• Installation
• Configuration
• Usage
• Troubleshooting
• License
• Contributing
• Contact
• Author

Features

• RAG (Retrieval Augmented Generation) - Keyword, semantic, and hybrid search functionality for PDF documents
• Dify External Knowledge API - Document search functionality via Dify’s external knowledge API
• Dify Workflow - Execute and retrieve results from Dify Workflow
• Web Search - Real-time web search using Tavily API
• Automatic JSON Generation - Automatically generate MCP JSON files needed for Claude Desktop and Cursor

Project Structure

.
├── case1                     # RAG example
├── case2                     # Dify External Knowledge API example
├── case3                     # Dify Workflow example
├── case4                     # Web Search example
├── data                      # Example data files
├── docs                      # Documentation folder
│   ├── case1.md           # case1 description 🚨 Includes tips for optimized tool invocation
│   ├── case2.md           # case2 description
│   ├── case3.md           # case3 description
│   ├── case4.md           # case4 description
│   └── installation.md    # Installation guide
├── .env.example              # .env example format
├── pyproject.toml            # Project settings
├── requirements.txt          # Required packages list
└── uv.lock                   # uv.lock

Requirements

• Python >= 3.11
• Claude Desktop or Cursor (MCP supporting version)
• uv (recommended) or pip

Installation

1. Clone the repository

git clone https://github.com/teddynote-lab/mcp.git
cd mcp

2. Set up virtual environment

Using uv (recommended)

# macOS/Linux
uv venv
uv pip install -r requirements.txt

# Windows
uv venv
uv pip install -r requirements_windows.txt

Using pip

python -m venv .venv

# Windows
.venv\Scripts\activate
pip install -r requirements_windows.txt

# macOS/Linux
source .venv/bin/activate

pip install -r requirements.txt

3. Preparing the PDF File

Plese prepare a PDF file required for RAG in the ./data directory.

Configuration