logsec-mcp-session-knowledge-base

LogSec MCP - Session Knowledge Management

Knowledge management system for AI session continuity, built as a Model Context Protocol (MCP) server.

Overview

LogSec provides persistent memory for AI assistants through a clean 3-tier architecture. The system enables context preservation across conversations with minimal overhead.

Core Features

• Session Persistence: SQLite-based storage for conversation history
• Project Organization: Isolated knowledge bases per project
• Search Capability: Keyword-based content retrieval
• Continuation System: Structured session handoffs
• Template Engine: Customizable response patterns

Installation

# Clone repository
git clone https://github.com/LevionLaurion/logsec-mcp-session-knowledge-base.git
cd LogSec

# Configure Claude Desktop
# Add to %APPDATA%\Claude\claude_desktop_config.json:
{
  "mcpServers": {
    "logsec": {
      "command": "python",
      "args": ["C:\\LogSec\\src\\logsec_core_v3.py"],
      "cwd": "C:\\LogSec"
    }
  }
}

# Restart Claude Desktop

Usage

Basic Commands

lo_start <project>     # Initialize session with continuation
lo_save <project>      # Save current context
lo_load <project>      # Load project knowledge
lo_update <project>    # Generate project documentation
lo_cont <project>      # Create continuation file

Examples

lo_start myproject
lo_save myproject "Implementation details for the API endpoint"
lo_load myproject "API"

Architecture

Directory Structure

LogSec/
├── src/
│   ├── logsec_core_v3.py    # Main MCP server (563 lines)
│   └── config/
│       └── config.json      # Configuration
├── data/
│   ├── projects/            # Project data
│   │   └── {project}/
│   │       ├── readme.md
│   │       └── continuation.md
│   ├── database/
│   │   └── logsec_phase3.db # Session storage
│   └── templates/           # Response templates
└── docs/
    └── DIRECTORY_STRUCTURE.md

Implementation

The system implements the Model Context Protocol with:

• JSON-RPC message handling
• Tool registration and dispatch
• Error handling and logging
• Template-based responses

Configuration

Configuration via src/config/config.json:

{
  "db_path": "C:\\LogSec\\data\\database\\logsec_phase3.db",
  "projects_dir": "C:\\LogSec\\data\\projects",
  "templates_dir": "C:\\LogSec\\data\\templates"
}

Development

Requirements

• Python 3.9+
• No external dependencies (uses stdlib only)
• Windows/Linux/macOS compatible

Testing

python -m unittest discover tests/

Contributing

1. Fork the repository
2. Create feature branch
3. Commit changes
4. Push to branch
5. Create Pull Request

License

MIT License - see LICENSE file for details.