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to process, extract text from, and merge invoice documents.","name","MCP Invoice","readme","# MCP Invoice\n\n这是一个使用 Python 开发的 MCP (Model Context Protocol) 服务器项目，专注于发票和收据处理的工具集合。该项目利用 OCR 技术实现发票识别、数据提取和 PDF 处理功能，为 AI 助手提供发票处理能力。\n\n## 功能特点\n\n- 发票和收据 OCR 处理：\n - 使用 macOS Vision framework 进行高精度文本识别\n - 支持处理单个 PDF 或图片文件（JPEG、PNG）\n - 支持批量处理目录下的所有发票和收据文件\n - 支持中英文 OCR 识别，适用于各类发票格式\n - 提供结构化数据提取，方便后续分析\n- PDF合并和管理功能：\n - 支持将多个发票或收据 PDF 文件合并为一个\n - 支持将多张发票图片（JPEG、PNG）合并为一个 PDF 文件\n - 支持混合合并不同格式的发票和收据\n- 高效的内存处理方式，减少磁盘 I/O，提高处理速度\n\n## MCP 部署指南\n\n### 环境要求\n\n- macOS 系统（支持 Vision framework）\n- Python 3.10 或更高版本\n- uv 依赖管理工具\n\n### 从 GitHub 安装\n\n1. 确保已安装 uv：\n\n```bash\npip install uv\n```\n\n2. 从 GitHub 克隆项目并安装依赖：\n\n```bash\ngit clone https://github.com/[username]/mcp-invoice.git\ncd mcp-invoice\nuv venv\nsource .venv/bin/activate\nuv pip install -e .\n```\n\n### 安装 PDF 处理依赖\n\npdf2image 需要系统上安装 Poppler：\n\n```bash\nbrew install poppler\n```\n\n### 部署为 MCP 服务\n\n有两种方式部署 MCP 服务：\n\n#### 1. 直接运行服务器\n\n```bash\n# 标准模式\nmcp-invoice\n\n# 或启用调试模式（包含文本位置信息）\nMCP_INVOICE_DEBUG=true mcp-invoice\n```\n\n#### 2. 使用 invoice_server.py 脚本\n\n```bash\n# 标准模式\npython invoice_server.py\n\n# 或启用调试模式\nMCP_INVOICE_DEBUG=true python invoice_server.py\n```\n\n### 配置为系统服务\n\n可以将 MCP 服务配置为系统服务，使其在系统启动时自动运行：\n\n1. 创建 LaunchAgent plist 文件：\n\n```bash\nmkdir -p ~/Library/LaunchAgents\ncat > ~/Library/LaunchAgents/com.user.mcp-invoice.plist << EOF\n\n\n\n\n Label\n com.user.mcp-invoice\n ProgramArguments\n \n $(which python)\n $(pwd)/invoice_server.py\n \n RunAtLoad\n \n KeepAlive\n \n StandardOutPath\n $(pwd)/logs/mcp-invoice.log\n StandardErrorPath\n $(pwd)/logs/mcp-invoice-error.log\n WorkingDirectory\n $(pwd)\n EnvironmentVariables\n \n PATH\n /usr/local/bin:/usr/bin:/bin:/usr/sbin:/sbin\n \n\n\nEOF\n\n# 创建日志目录\nmkdir -p logs\n\n# 加载服务\nlaunchctl load ~/Library/LaunchAgents/com.user.mcp-invoice.plist\n```\n\n2. 启动服务：\n\n```bash\nlaunchctl start com.user.mcp-invoice\n```\n\n3. 停止服务：\n\n```bash\nlaunchctl stop com.user.mcp-invoice\n```\n\n## AI 编辑器集成\n\n### 在 Cursor 中配置 MCP\n\n在 Cursor 编辑器中，可以通过以下配置添加 MCP Invoice 服务：\n\n1. 打开 Cursor 的 MCP 配置文件：\n - macOS: `$HOME/Library/Application Support/Cursor/tools/tools.json`\n - Linux: `$HOME/.config/Cursor/tools/tools.json`\n - Windows: `%APPDATA%\\Cursor\\tools\\tools.json`\n\n2. 在 `tools.json` 文件中添加 MCP Invoice 服务配置：\n\n```json\n{\n \"tools\": {\n \"invoice\": {\n \"command\": \"uv\",\n \"args\": [\n \"--directory\",\n \"/path/to/mcp-invoice\",\n \"run\",\n \"invoice_server.py\"\n ],\n \"env\": {\n \"MCP_INVOICE_DEBUG\": \"false\"\n },\n \"alwaysAllow\": [\n \"process_file\",\n \"process_directory\",\n \"merge_pdfs\"\n ]\n }\n }\n}\n```\n\n3. 重启 Cursor 后，你可以在 AI 助手中直接请求使用功能，例如：\n \"请使用 OCR 工具读取文件：/path/to/document.pdf\"\n \"请合并这些 PDF 文件：/path/to/file1.pdf, /path/to/file2.pdf\"\n\n### 在 Cline 中配置 MCP\n\nCline 与 MCP 集成方法类似于 Cursor：\n\n1. 更新 Cline 配置文件来添加此 MCP 工具\n2. 重启 Cline 客户端\n3. 使用与 Cursor 相同的方式来请求处理发票文件\n\n### 在 Roocode 中配置 MCP\n\n在 Roocode 中集成 MCP Invoice 服务：\n\n1. 按照 Roocode 文档配置外部工具\n2. 指向已部署的 MCP Invoice 服务\n3. 在 Roocode 中使用自然语言请求处理发票文件\n\n## MCP 服务调试\n\n1. 启用详细日志：\n\n```bash\nMCP_INVOICE_DEBUG=true mcp-invoice\n```\n\n2. 检查服务是否正常运行：\n\n```bash\nps aux | grep mcp-invoice\n```\n\n3. 查看日志：\n\n```bash\ntail -f logs/mcp-invoice.log\n```\n\n## 使用方法\n\nMCP 服务器提供以下主要工具：\n\n1. `process_file`: 处理单个文件并提取文本\n - 参数：`file_path` - 文件的绝对路径\n - 返回：包含文件路径和提取文本的字典\n\n2. `process_directory`: 处理一个目录中的所有 PDF 和图片文件\n - 参数：`directory_path` - 目录的绝对路径\n - 返回：包含每个文件路径和提取文本的字典列表\n\n3. `merge_pdfs`: 合并多个PDF和/或图片文件为一个PDF\n - 参数：`file_paths` - 要合并的文件路径列表\n - 参数：`output_path` - 输出PDF的路径\n - 返回：合并后PDF的路径\n\n## 开发和扩展\n\n本项目使用 uv 进行依赖管理，使用 hatch 进行构建。\n\n### 开发环境设置\n\n1. 创建虚拟环境：\n\n```bash\nuv venv\nsource .venv/bin/activate\n```\n\n2. 安装开发依赖：\n\n```bash\nuv pip install -e \".[dev]\"\n```\n\n## 故障排除\n\n1. **Vision framework 错误**\n - 确保使用 macOS 系统\n - 确保已安装 pyobjc-framework-vision 11.0 或更高版本\n\n2. **UTF-8 编码问题**\n - 所有 OCR 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