Kiro MCP Memory
An enhanced MCP (Model Context Protocol) server for intelligent memory and task management, designed for AI assistants and development workflows. Features semantic search, automatic task extraction, knowledge graphs, and comprehensive project management.
✨ Key Features
🧠 Intelligent Memory Management
- Semantic search using sentence-transformers for natural language queries
- Automatic memory classification with importance scoring
- Duplicate detection and content deduplication
- File path associations for code-memory relationships
- Knowledge graph relationships with automatic similarity detection
📋 Advanced Task Management
- Auto-task extraction from conversations and code comments
- Priority and category management with validation
- Status tracking (pending, in_progress, completed, cancelled)
- Task-memory relationships in knowledge graph
- Project-based organization
🔧 Enterprise Features
- Performance monitoring with detailed metrics
- Health checks and system diagnostics
- Automatic cleanup of old data and duplicates
- Database optimization tools
- Comprehensive logging and error tracking
🚀 Easy Deployment
- uvx compatible for one-command installation
- Zero-configuration startup with sensible defaults
- Environment variable configuration
- Cross-platform support (Windows, macOS, Linux)
🏗️ Project Structure
kiro-mcp-memory/
├── mcp_server_enhanced.py # Main MCP server
├── memory_manager.py # Core memory/task logic
├── database.py # Database operations
├── requirements.txt # Python dependencies
├── setup.py # Package configuration
├── data/ # SQLite database storage
├── logs/ # Application logs
└── tests/ # Test files
🚀 Quick Start
Option 1: Using uvx (Recommended)
# Install and run with uvx
uvx kiro-mcp-memory
Option 2: Manual Installation
# Clone and install
git clone https://github.com/cbunting99/kiro-mcp-memory.git
cd kiro-mcp-memory
pip install -e .
# Run the server
kiro-mcp-memory
Option 3: Development Setup
# Clone repository
git clone https://github.com/cbunting99/kiro-mcp-memory.git
cd kiro-mcp-memory
# Install dependencies
pip install -r requirements.txt
# Run directly
python mcp_server_enhanced.py
⚙️ MCP Configuration
Add to your MCP client configuration:
For uvx installation:
{
"mcpServers": {
"memory-manager": {
"command": "uvx",
"args": ["kiro-mcp-memory"],
"env": {
"LOG_LEVEL": "INFO",
"MAX_MEMORY_ITEMS": "1000",
"ENABLE_AUTO_CLEANUP": "true"
}
}
}
}
For local installation:
{
"mcpServers": {
"memory-manager": {
"command": "python",
"args": ["mcp_server_enhanced.py"],
"cwd": "/path/to/kiro-mcp-memory",
"env": {
"LOG_LEVEL": "INFO",
"MAX_MEMORY_ITEMS": "1000",
"ENABLE_AUTO_CLEANUP": "true"
}
}
}
}
🛠️ Available Tools
Core Memory Tools
get_memory_context(query)- Get relevant memories and contextcreate_task(title, description, priority, category)- Create new tasksget_tasks(status, limit)- Retrieve tasks with filteringget_project_summary()- Get comprehensive project overview
System Management Tools
health_check()- Check server health and connectivityget_performance_stats()- Get detailed performance metricscleanup_old_data(days_old)- Clean up old memories and tasksoptimize_memories()- Remove duplicates and optimize storageget_database_stats()- Get comprehensive database statistics
🔧 Configuration Options
Configure via environment variables:
| Variable | Default | Description |
|---|---|---|
LOG_LEVEL |
INFO |
Logging level (DEBUG, INFO, WARNING, ERROR) |
MAX_MEMORY_ITEMS |
1000 |
Maximum memories per project |
CLEANUP_INTERVAL_HOURS |
24 |
Auto-cleanup interval |
ENABLE_AUTO_CLEANUP |
true |
Enable automatic cleanup |
MAX_CONCURRENT_REQUESTS |
5 |
Max concurrent requests |
REQUEST_TIMEOUT |
30 |
Request timeout in seconds |
🧪 Testing
Run the test suite to verify functionality:
# Run all tests
python test_enhanced_features.py
python test_new_project_system.py
python test_project_tools.py
# Test MCP protocol
python test_mcp_protocol.py
📊 Performance & Monitoring
The server includes built-in performance tracking:
- Response time monitoring for all tools
- Success rate tracking with error counts
- Memory usage statistics
- Database performance metrics
- Automatic health checks
Access via the get_performance_stats() and health_check() tools.
🗄️ Database
- SQLite for reliable, file-based storage
- Automatic schema migrations for updates
- Comprehensive indexing for fast queries
- Built-in backup and optimization tools
- Cross-platform compatibility
Default location: ./data/mcp_memory.db
🔍 Semantic Search
Powered by sentence-transformers for intelligent memory retrieval:
- Natural language queries - "Find memories about database optimization"
- Similarity-based matching using embeddings
- Configurable similarity thresholds
- Automatic model downloading (~90MB on first run)
📝 Logging
Comprehensive logging system:
- Daily log rotation in
./logs/directory - Structured logging with timestamps and levels
- Performance tracking integrated
- Error tracking with stack traces
🤝 Contributing
- Fork the repository
- Create a feature branch
- Add tests for new functionality
- Ensure all tests pass
- Submit a pull request
📄 License
MIT License - see LICENSE file for details.
🆘 Support
- Issues: GitHub Issues
- Documentation: README
- Discussions: GitHub Discussions
🏷️ Version History
- v1.2.0 - Enhanced MCP server with performance monitoring and health checks
- v1.1.0 - Added semantic search and knowledge graph features
- v1.0.0 - Initial release with basic memory and task management
Metadata
Release files for kiro-mcp-memory 1.2.1
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| kiro_mcp_memory-1.2.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 52.2 kB
Release files / kiro_mcp_memory-1.2.1.tar.gz
| Download URL | kiro_mcp_memory-1.2.1.tar.gz |
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