📄 Document Analyzer MCP Server
让 AI 读懂任何复杂文档 - 解决 AI 上下文限制问题的 MCP 服务器 Make AI understand complex documents - MCP server solving AI context limitations
🌍 语言 / Language
中文文档
🎯 核心功能
- ✅ 智能文档分析 - 自动识别章节结构、处理合并单元格
- ✅ 多格式支持 - Excel (.xlsx, .xls) | PDF/Word 开发中
- ✅ 精确字段定位 - 字段映射表 + 章节级别读取
- ✅ 高效性能 - 结构化缓存 + 按需加载
🚀 快速开始
安装
macOS / Linux (推荐使用 pipx)
# 安装 pipx
brew install pipx # macOS
# 或 sudo apt install pipx # Ubuntu/Debian
# 安装 doc-mcp-server
pipx install doc-mcp-server
Windows
pip install doc-mcp-server
更多安装方式请查看 完整安装教程
配置 Claude Code
在 ~/.claude.json 或项目根目录的配置文件中添加:
{
"mcpServers": {
"document-analyzer": {
"command": "doc-mcp-server"
}
}
}
详细配置请查看 快速开始指南
📚 完整文档
💡 使用示例
# 1. 分析文档结构
analyze_document(file_path="/path/to/document.xlsx")
# 2. 读取特定章节
read_section(file_path="/path/to/document.xlsx", section_name="第一部分")
# 3. 读取单个字段
read_field(file_path="/path/to/document.xlsx", field_key="第一部分_企业名称")
🤝 贡献与反馈
- 问题反馈: GitHub Issues
- 贡献代码: CONTRIBUTING.md
English Documentation
🎯 Key Features
- ✅ Smart Document Analysis - Auto-detect sections, handle merged cells
- ✅ Multi-format Support - Excel (.xlsx, .xls) | PDF/Word in development
- ✅ Precise Field Mapping - Field mapping table + section-level reading
- ✅ High Performance - Structured caching + lazy loading
🚀 Quick Start
Installation
macOS / Linux (Recommended with pipx)
# Install pipx
brew install pipx # macOS
# or sudo apt install pipx # Ubuntu/Debian
# Install doc-mcp-server
pipx install doc-mcp-server
Windows
pip install doc-mcp-server
For more installation options, see Full Installation Guide
Configure Claude Code
Add to ~/.claude.json or your project's config file:
{
"mcpServers": {
"document-analyzer": {
"command": "doc-mcp-server"
}
}
}
For detailed configuration, see Quick Start Guide
📚 Full Documentation
- Installation Guide - Platform-specific installation steps
- Update Guide - How to upgrade to the latest version
- Quick Start - Configuration and basic usage
- Usage Guide - Complete API and examples
- Troubleshooting - Common issues and solutions
💡 Usage Example
# 1. Analyze document structure
analyze_document(file_path="/path/to/document.xlsx")
# 2. Read specific section
read_section(file_path="/path/to/document.xlsx", section_name="Section 1")
# 3. Read single field
read_field(file_path="/path/to/document.xlsx", field_key="Section1_CompanyName")
🤝 Contributing & Feedback
- Report Issues: GitHub Issues
- Contribute Code: CONTRIBUTING.md
📄 License
MIT License - see LICENSE for details
Made with ❤️ by Yang Jiahui
Metadata
Release files for doc-mcp-server 0.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| doc_mcp_server-0.1.2.tar.gz | 21.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| doc_mcp_server-0.1.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 36.6 kB
Release files / doc_mcp_server-0.1.2.tar.gz
| Download URL | doc_mcp_server-0.1.2.tar.gz |
|---|---|
| Size | 21.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.13.3
|
Release files / doc_mcp_server-0.1.2-py3-none-any.whl
| Download URL | doc_mcp_server-0.1.2-py3-none-any.whl |
|---|---|
| Size | 15.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.13.3
|