Literature Memory

🚀 Ongoing Project

A flexible system for managing various types of sources (papers, books, web pages, etc.) and integrating them with a knowledge graph.

✨ Features

Core Features

• A unified source identifier system using an internal UUID system.
• Supports multiple source types (papers, web pages, books, videos, blogs).
• Each source supports multiple identifiers (arXiv, DOI, Semantic Scholar, ISBN, URL).
• Structured note - taking function with support for titles and content.
• Tracks the status of sources (unread, reading, completed, archived).

Entity Integration

• Links sources to knowledge graph entities.
• Tracks the relationships between sources and entities.
• Supports flexible relationship types (discuss, introduce, extend, assess, etc.).
• Integrates a memory graph function.

📦 Prerequisites

This system is integrated with the MCP Memory Server for persistent knowledge graph storage.

🚀 Quick Start

1. Create a new SQLite database using our schema:

# Create a new database
sqlite3 sources.db < create_sources_db.sql

2. Install the source management server:

# Install for Claude Desktop, specifying the database path
fastmcp install source - manager - server.py --name "Source Manager" -e SQLITE_DB_PATH=/path/to/sources.db

🔧 Technical Details

Core Table Structure

-- Source table
CREATE TABLE sources (
    id UUID PRIMARY KEY,
    title TEXT NOT NULL,
    type TEXT CHECK(type IN ('paper', 'webpage', 'book', 'video', 'blog')) NOT NULL,
    identifiers JSONB NOT NULL,
    status TEXT CHECK(status IN ('unread', 'reading', 'completed', 'archived')) DEFAULT 'unread'
);

-- Source notes
CREATE TABLE source_notes (
    source_id UUID REFERENCES sources(id),
    note_title TEXT NOT NULL,
    content TEXT NOT NULL,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    PRIMARY KEY (source_id, note_title)
);

-- Entity links
CREATE TABLE source_entity_links (
    source_id UUID REFERENCES sources(id),
    entity_name TEXT,
    relation_type TEXT CHECK(relation_type IN ('discuss', 'introduce', 'extend', 'assess', etc.)),
    PRIMARY KEY (source_id, entity_name)
);

💻 Usage Examples

Basic Usage

# Add a new source
add_source("example_paper.pdf", "paper")

# Fuzzy match and add an identifier
fuzzy_match_and_add_identifier("related_work.pdf", "arXiv")

Advanced Usage

# Establish a relationship between a source and an entity
link_source_to_entity(source_id, entity_name, relation_type)

# View all associated entities
get_associated_entities(source_id)

💡 Best Practices

1. Data Organization: Categorize sources by type and use structured notes to record key information.
2. Status Management: Regularly update the status of sources to ensure tracking of the latest progress.
3. Identifier Management: Add as many identifiers as possible to each source for easy retrieval and association later.

🔧 Technical Details

1. Data Matching: Uses a fuzzy matching algorithm to identify sources based on titles and types.
2. Scalability: Supports custom relationship types and entity classifications for personalized needs.
3. Performance Optimization: Optimizes query speed through indexing to ensure efficient data retrieval.

🤝 Contribution Guidelines

1. Join the Project: Visit our repository page to learn how to join the team.
2. Create Feature Branches: Develop independent code branches for new features.
3. Add Test Cases: Ensure that new features pass comprehensive test validations.
4. Submit Pull Requests: Contribute your changes to the main project.