Smart Document Helper Mcp
What is Smart Document Helper Mcp
Smart-Document-Helper-MCP is an intelligent document processing application powered by AI, utilizing Gradio and implementing the Model Context Protocol (MCP) for seamless integration.
Use cases
Use cases include summarizing academic papers, processing business reports and contracts, extracting insights from large text documents, and creating study materials.
How to use
To use Smart-Document-Helper-MCP, clone the repository, install the required dependencies, set up system dependencies, and launch the application using the provided scripts.
Key features
Key features include a Document Summarizer for AI-powered text summarization, an interactive Chat with Documents for context-aware Q&A, and a Mindmap Generator for creating visual representations of documents.
Where to use
Smart-Document-Helper-MCP can be used in various fields such as research, business, content analysis, and education.
Overview
What is Smart Document Helper Mcp
Smart-Document-Helper-MCP is an intelligent document processing application powered by AI, utilizing Gradio and implementing the Model Context Protocol (MCP) for seamless integration.
Use cases
Use cases include summarizing academic papers, processing business reports and contracts, extracting insights from large text documents, and creating study materials.
How to use
To use Smart-Document-Helper-MCP, clone the repository, install the required dependencies, set up system dependencies, and launch the application using the provided scripts.
Key features
Key features include a Document Summarizer for AI-powered text summarization, an interactive Chat with Documents for context-aware Q&A, and a Mindmap Generator for creating visual representations of documents.
Where to use
Smart-Document-Helper-MCP can be used in various fields such as research, business, content analysis, and education.
Content
🧠 SmartDoc MCP - Document Intelligence App
A powerful multi-function document analysis tool built with Gradio, supporting:
- 📄 Document Summarization (Nebius Qwen / Pegasus fallback)
- ❓ Question Answering
- 🌐 Flowchart (Graphviz DOT code) generation
🚀 Features
| Functionality | Description |
|---|---|
| 📂 File Upload | Supports .pdf, .docx, .txt |
| 📝 Direct Text Input | Summarize or ask questions on raw text |
| 📄 AI Summarization | Uses Qwen 2.5 32B (via Nebius) or Google Pegasus |
| ❓ QA on Text | Uses roberta-base-squad2 from HuggingFace |
| 🌐 Flowchart Builder | Visual summary of key points via Graphviz |
| 🔁 Fallback Logic | Automatically switches to Pegasus if Nebius fails |
⚙️ Technologies Used
- Gradio — UI Framework
- Nebius AI Studio — Qwen summarization
- Transformers (Hugging Face) — For Pegasus & QA
- Graphviz — Flowchart rendering
- PyMuPDF (
fitz) — PDF text extraction - python-docx — Word file reader
- OpenAI Python SDK — Nebius-compatible
🔐 .env Configuration
Create a .env file in your root directory with:
NEBIUS_API_KEY=your_actual_api_key_here MODEL_ID=Qwen/Qwen2.5-32B-Instruct
- Clone the repository:
git clone <your-repo-url>
cd Smart_Document_Helper_MCP
- Install dependencies:
pip install -r requirements.txt
- Install system dependencies (Ubuntu/Debian):
sudo apt-get update && sudo apt-get install -y graphviz libgl1-mesa-glx libglib2.0-0
- Launch the application:
python main.py
Server Deployment
- Make the launch script executable:
chmod +x launch.sh
- Run the launch script:
./launch.sh
System Requirements
- Python 3.8+
- 8GB RAM minimum
- GPU recommended for better performance