📚 Literature Manager MCP
A beginner-friendly system for managing research papers, books, and other sources using AI assistants through the Model Context Protocol (MCP).
🎯 What is this?
This tool helps you:
- Organize research papers, books, websites, and videos
- Take notes on your sources with structured titles
- Track reading progress (unread, reading, completed, archived)
- Connect sources to concepts in your knowledge base
- Work with AI assistants like Claude to manage your literature
🚀 Quick Start
1. Prerequisites
- Python 3.8 or higher
🚀 Quick Start
1. Prerequisites
- Python 3.8 or higher
- Basic familiarity with command line
2. Installation
# Clone this repository
git clone https://github.com/Amruth22/literature-manager-mcp.git
cd literature-manager-mcp
# Install dependencies
pip install -r requirements.txt
# Create your database
python setup_database.py
3. Choose Your Usage Method
Option A: Direct Python Usage (Recommended)
# Set your database path
## 📚 How to Use
### Command Line Interface
```bash
# Add a research paper
python cli.py add-source "Attention Is All You Need" paper arxiv 1706.03762
# Add a book
python cli.py add-source "Deep Learning" book isbn 978-0262035613
# Add a note
python cli.py add-note "Attention Is All You Need" paper arxiv 1706.03762 \
"Key Insight" "Transformers eliminate recurrence"
# Update status
python cli.py update-status "Attention Is All You Need" paper arxiv 1706.03762 completed
# Link to entity
python cli.py link-entity "Attention Is All You Need" paper arxiv 1706.03762 \
"transformer architecture" introduces
# List sources
python cli.py list --type paper --status unread
# Search sources
python cli.py search "transformer"
# Show statistics
python cli.py stats
# Get help
python cli.py help
Direct Python Usage
from src.database import LiteratureDatabase
# Initialize database
db = LiteratureDatabase("literature.db")
# Add a source
source_id = db.add_source(
title="Attention Is All You Need",
source_type="paper",
identifier_type="arxiv",
identifier_value="1706.03762"
# Add a note
db.add_note(source_id, "Key Insight", "Transformers eliminate recurrence...")
# Update status
db.update_status(source_id, "completed")
# Link to entity
db.link_to_entity(source_id, "transformer architecture", "introduces")
# Get source details
source = db.get_source_by_id(source_id)
print(source)
Running Examples
# Run basic examples
python examples/basic_usage.py
# Run advanced examples
python examples/advanced_usage.py
# Run direct usage examples
python direct_usage.py
- completed: Finished reading
- archived: Saved for later reference
🔗 Relationship Types
When linking sources to concepts:
- discusses: Source talks about the concept
- introduces: Source first presents the concept
- extends: Source builds upon the concept
- evaluates: Source analyzes/critiques the concept
- applies: Source uses the concept practically
- critiques: Source criticizes the concept
🛠️ Available Commands
Basic Operations
add_source()- Add a new sourceadd_note()- Add notes to sourcesupdate_status()- Change reading statussearch_sources()- Find sources
Advanced Operations
link_to_entity()- Connect sources to conceptsget_entity_sources()- Find sources by conceptadd_identifier()- Add more IDs to existing sources
Database Operations
list_sources()- Show all sourcesget_source_details()- Get complete source infodatabase_stats()- Show database statistics
📁 Project Structure
literature-manager-mcp/
├── README.md # This file
├── requirements.txt # Python dependencies
├── setup_database.py # Database setup script
├── server.py # Main MCP server
├── src/
│ ├── __init__.py
│ ├── database.py # Database operations
│ ├── models.py # Data models
│ ├── tools.py # MCP tools
│ └── utils.py # Helper functions
├── examples/
│ ├── basic_usage.py # Simple examples
│ └── advanced_usage.py # Complex workflows
├── tests/
│ └── test_basic.py # Unit tests
└── docs/
├── installation.md # Detailed setup
├── examples.md # More examples
└── troubleshooting.md # Common issues
🤝 Contributing
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
📝 License
This project is licensed under the MIT License - see the LICENSE file for details.
🆘 Need Help?
- Check the troubleshooting guide
- Look at examples
- Open an issue
🙏 Acknowledgments
- Based on the original work by zongmin-yu
- Built with FastMCP
- Uses Model Context Protocol