redis-mcp-server3 1.1.0

A Model Context Protocol (MCP) server that enables secure interaction with Redis DataBases.

Redis MCP Server

A Model Context Protocol (MCP) server that enables secure, efficient interaction with Redis databases through AI assistants and applications.

🚀 Features

• 🔌 MCP Protocol Support: Built on FastMCP framework with standard MCP tools and resources
• 🗄️ Redis Compatibility: Support for Redis single, master-slave, and cluster deployments
• ⚡ Asynchronous Architecture: Built with redis.asyncio and hiredis for high-performance operations
• 🔗 Connection Pooling: Efficient connection management with configurable pool settings
• 🔒 Security Features: Password protection, SSL support, and connection validation
• 🛠️ Comprehensive Tools: Redis command execution, monitoring, and data management
• 📊 Monitoring & Analytics: Server info, memory usage, client connections, and key statistics
• 🔧 Flexible Configuration: JSON-based configuration with multiple instance support
• 📝 Detailed Logging: Structured logging with configurable levels and file rotation
• 🐳 Production Ready: Health checks, error handling, and graceful connection management

📋 Prerequisites

• Python: >= 3.12
• Redis: >= 5.0.0
• Network Access: To Redis server instance(s)

🛠️ Installation

1. Install from PyPI (Recommended)

pip install redis-mcp-server3

2. Configure database connection

Edit dbconfig.json with your database credentials:

{
  "redisEncoding": "utf-8",
  "redisPoolSize": 5,
  "redisMaxConnections": 10,
  "redisConnectionTimeout": 30,
  "socketTimeout": 30,
  "retryOnTimeout": true,
  "healthCheckInterval": 30,
  "redisType-Comment": "single 单机模式、masterslave 主从模式、cluster 集群模式",
  "redisList": [
    {
      "redisInstanceId": "redis-local-single",
      "redisType": "single",
      "redisHost": "localhost",
      "redisPort": 6379,
      "redisDatabase": 0,
      "redisPassword": 123456,
      "dbActive": true
    },
    {
      "redisInstanceId": "redis-ms-single",
      "redisType": "masterslave",
      "redisHost": "localhost",
      "redisPort": 6379,
      "redisDatabase": 0,
      "redisPassword": 123456,
      "dbActive": false
    },
    {
      "redisInstanceId": "redis-cluster-single",
      "redisType": "cluster",
      "redisHost": "localhost",
      "redisPort": 6379,
      "redisDatabase": 0,
      "redisPassword": 123456,
      "dbActive": false
    }
  ],
  "logPath": "/path/to/logs",
  "logLevel": "info"
}
# redisType
Redis Instance is in single、masterslave、cluster mode.
# dbActive
Only database instances with dbActive set to true in the dbList configuration list are available. 
# logPath
MCP server log is stored in /path/to/logs/mcp_server.log.
# logLevel
TRACE, DEBUG, INFO, SUCCESS, WARNING, ERROR, CRITICAL

3. Configure MCP Client

Add to your MCP client configuration file:

{
  "mcpServers": {
    "redis-mcp-client": {
      "command": "redis-mcp-server3",
      "env": {
        "config_file": "/path/to/your/dbconfig.json"
      },
      "disabled": false
    }
  }
}

Note: Replace /path/to/your/dbconfig.json with the actual path to your configuration file.

4. Clone the repository (Development Mode)

git clone https://github.com/j00131120/mcp_database_server.git
cd mcp_database_server/redis_mcp_server
# Import project into your IDE

5. Configure MCP Client for Development

{
  "mcpServers": {
    "redis-mcp-client": {
      "command": "/bin/uv",
      "args": ["run", "redis_mcp_server3/server.py"],
      "cwd": "/path/to/your/project",
      "env": {
        "config_file": "/path/to/your/dbconfig.json"
      },
      "disabled": false
    }
  }
}

# command
uv absolute path
# cwd
project absolute path
# config_file
dbconfig.json file path

🚀 Quick Start

1. Start the MCP Server

# Using installed package
redis-mcp-server3

# Using FastMCP CLI
fastmcp run redis_mcp_server3/server.py

# Direct Python execution
python redis_mcp_server3/server.py

# Using fastmcp debug
fastmcp dev redis_mcp_server3/server.py

2. Basic Usage Examples

# Execute Redis commands
await redis_exec("SET", ["user:1001", "John Doe"])
await redis_exec("GET", ["user:1001"])

# Hash operations
await redis_exec("HSET", ["user:1001:profile", "name", "John", "age", "30"])
await redis_exec("HGETALL", ["user:1001:profile"])

# List operations
await redis_exec("LPUSH", ["tasks", "task1", "task2"])
await redis_exec("LRANGE", ["tasks", "0", "-1"])

# Get server information
server_info = await get_server_info()
memory_info = await get_memory_info()

📚 API Reference

MCP Tools

redis_exec(command: str, args: list = None)

Execute any Redis command with arguments.

Parameters:

• command (str): Redis command name (e.g., 'GET', 'SET', 'HGET')
• args (list, optional): Command arguments

Returns:

• dict: Execution result with success status and data

Examples:

# String operations
await redis_exec("SET", ["key1", "value1"])
await redis_exec("GET", ["key1"])
await redis_exec("SETEX", ["key2", "60", "temp_value"])

# Hash operations  
await redis_exec("HSET", ["hash1", "field1", "value1"])
await redis_exec("HGETALL", ["hash1"])

# List operations
await redis_exec("LPUSH", ["list1", "item1", "item2"])
await redis_exec("LRANGE", ["list1", "0", "-1"])

# Set operations
await redis_exec("SADD", ["set1", "member1", "member2"])
await redis_exec("SMEMBERS", ["set1"])

gen_test_data(table: str, columns: list, num: int = 10)

Generate test data for Redis hash structures.

Parameters:

• table (str): Table/prefix name for the keys
• columns (list): Field names to populate
• num (int): Number of test records to generate

get_server_info()

Get Redis server basic information.

Returns:

• Server version, mode, OS, architecture, uptime

get_memory_info()

Get Redis memory usage statistics.

Returns:

• Memory usage, peak usage, RSS memory, max memory settings

get_clients_info()

Get Redis client connection information.

Returns:

• Connected clients count, input/output buffer sizes

get_stats_info()

Get Redis operation statistics.

Returns:

• Total connections, commands processed, keyspace hits/misses

get_db_info()

Get Redis database information.

Returns:

• Database size, keyspace information

get_keys_info()

Get sample key information (first 10 keys).

Returns:

• Total key count, sample keys with types and TTL

get_key_types()

Get key type distribution statistics.

Returns:

• Distribution of different key types (string, hash, list, set, zset)

get_redis_config()

Get Redis configuration information.

Returns:

• Important Redis configuration parameters

get_redis_overview()

Get comprehensive Redis overview (all monitoring information).

Returns:

• Complete system overview including all above information

MCP Resources

database://config

Database configuration information (sensitive data hidden).

Returns:

• Safe configuration details without passwords

database://status

Database connection status and health check results.

Returns:

• Connection status, ping results, basic operations test

🏗️ Architecture

Project Structure

redis_mcp_server/
├── src/
│   ├── __init__.py              # Package metadata and API
│   ├── server.py                # Main MCP server entry point
│   ├── utils/                   # Utility modules
│   │   ├── __init__.py          # Utility exports
│   │   ├── db_config.py         # Configuration management
│   │   ├── db_pool.py           # Connection pool management
│   │   ├── db_operate.py        # Redis operations wrapper
│   │   └── logger_util.py       # Logging configuration
│   ├── resources/               # MCP resources
│   │   └── db_resources.py      # Database resources provider
│   └── tools/                   # MCP tools
│       └── db_tool.py           # Redis management tools
├── dbconfig.json               # Database configuration
├── pyproject.toml              # Project configuration
├── requirements.txt            # Python dependencies
└── README.md                   # Project documentation

Key Components

Connection Pool Manager

• Singleton Pattern: Single pool instance per application
• Async Management: Non-blocking connection handling
• Health Monitoring: Automatic connection validation
• Resource Cleanup: Proper connection release

Configuration System

• JSON-based: Human-readable configuration
• Environment Override: Flexible deployment options
• Multi-instance: Support for multiple Redis instances
• Validation: Comprehensive error checking

Logging System

• Structured Logging: JSON-formatted log entries
• File Rotation: Automatic log file management
• Configurable Levels: TRACE to CRITICAL
• Performance Optimized: Asynchronous logging

🔧 Advanced Configuration

SSL/TLS Configuration

For secure connections, configure SSL in your dbconfig.json:

{
  "redisList": [
    {
      "redisInstanceId": "secure-redis",
      "redisHost": "secure.redis.example.com",
      "redisPort": 6380,
      "redisSsl": true,
      "redisPassword": "secure_password",
      "dbActive": true
    }
  ]
}

Cluster Configuration

For Redis cluster deployments:

{
  "redisList": [
    {
      "redisInstanceId": "redis-cluster",
      "redisType": "cluster",
      "redisHost": "cluster-node1.example.com",
      "redisPort": 7000,
      "redisPassword": "cluster_password",
      "dbActive": true
    }
  ]
}

Performance Tuning

Optimize for high-throughput scenarios:

{
  "redisPoolSize": 20,
  "redisMaxConnections": 50,
  "redisConnectionTimeout": 10,
  "socketTimeout": 5,
  "healthCheckInterval": 60
}

🧪 Testing

Basic Connection Test

# Test Redis connection
status = await get_connection_status()
print(status)  # {'ping': True, 'set_get': 'ok'}

Performance Testing

# Generate test data
await gen_test_data("users", ["name", "email", "age"], 1000)

# Check database size
db_info = await get_db_info()
print(f"Total keys: {db_info['dbsize']}")

📊 Monitoring

Health Checks

The server provides built-in health monitoring:

# Get comprehensive overview
overview = await get_redis_overview()

# Check specific metrics
memory = await get_memory_info()
if memory['used_memory'] > threshold:
    # Handle high memory usage
    pass

Log Analysis

Monitor server logs for performance and errors:

# View real-time logs
tail -f /var/log/redis_mcp_server/logs/mcp_server.log

# Search for errors
grep "ERROR" /var/log/redis_mcp_server/logs/mcp_server.log

🚨 Troubleshooting

Common Issues

Connection Errors

Problem: ConnectionError: Connection refused

Solution:

# Check Redis server status
redis-cli ping

# Verify Redis is running
systemctl status redis

# Check network connectivity
telnet localhost 6379

Authentication Errors

Problem: AuthenticationError: Auth failed

Solutions:

• Verify password in dbconfig.json
• Check Redis AUTH configuration
• Ensure user has proper permissions

Memory Issues

Problem: High memory usage or OOM errors

Solutions:

• Monitor with get_memory_info()
• Adjust maxmemory policy
• Implement key expiration
• Use Redis memory optimization techniques

Performance Issues

Problem: Slow response times

Solutions:

• Increase connection pool size
• Reduce connection timeout
• Monitor with get_stats_info()
• Check network latency

Debug Mode

Enable debug logging:

{
  "logLevel": "debug"
}

Diagnostic Commands

# Check server health
server_info = await get_server_info()
clients_info = await get_clients_info()
stats_info = await get_stats_info()

# Analyze key distribution
key_types = await get_key_types()
keys_sample = await get_keys_info()

🤝 Contributing

We welcome contributions! Please follow these guidelines:

Development Setup

# Clone the repository
git clone https://github.com/j00131120/mcp_database_server.git
cd mcp_database_server/redis_mcp_server

# Install development dependencies
pip install -e ".[dev,test,docs]"

# Install pre-commit hooks
pre-commit install

Code Quality

# Format code
black redis_mcp_server3/
isort redis_mcp_server3/

# Lint code
flake8 redis_mcp_server3/
mypy redis_mcp_server3/

# Run tests
pytest

# Run tests with coverage
pytest --cov=redis_mcp_server3 --cov-report=html

Submitting Changes

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Make your changes
4. Add tests for new functionality
5. Ensure all tests pass
6. Commit your changes (git commit -m 'Add amazing feature')
7. Push to the branch (git push origin feature/amazing-feature)
8. Open a Pull Request

Code Style

• Follow PEP 8 guidelines
• Use type hints for all functions
• Add docstrings for public methods
• Write comprehensive tests
• Update documentation

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

👥 Authors

• Frank Jin - Initial work - [e-mail]

🙏 Acknowledgments

• FastMCP - MCP framework foundation
• redis-py - Python Redis client
• Loguru - Structured logging library
• Redis - In-memory data structure store

📞 Support

• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Email: [e-mail]

🔄 Version History

v1.0.0

• Initial release
• Full MCP protocol support
• Redis connection pooling
• Comprehensive monitoring tools
• Security features implementation
• Production-ready deployment

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