MySQL MCP Server 🚀

An intelligent MySQL MCP Server with enterprise data federation capabilities, enabling LLMs to query and analyze data across multiple disparate MySQL data sources. Goes beyond basic querying to provide comprehensive business intelligence, cross-system data correlation, and federated analytics with high-performance caching.

✨ Features

🏢 Enterprise Data Federation

• 🌐 Multi-source MySQL access: Connect to completely different business systems (CRM, ERP, E-commerce, etc.)

• 🧠 Intelligent source classification: Automatically identify and catalog CRM, E-commerce, ERP, Marketing, Support systems

• 🔗 Cross-source query engine: Execute federated queries combining data from multiple business systems

• 📊 360° business intelligence: Complete customer view across all touchpoints and systems

• 🔍 Relationship detection: Find connections between disparate systems (shared customer IDs, etc.)

📈 Advanced Analytics & Intelligence

• 👥 User behavior federation: Track customers across CRM → Marketing → E-commerce → Support journey

• 💼 Business process analytics: End-to-end analysis from procurement → inventory → sales → finance

• 🎯 Revenue attribution: Multi-touch attribution across marketing, sales, and customer systems

• 🔄 Data consistency auditing: Compare and validate data integrity across business systems

• 📈 Cross-system KPI reporting: Unified executive dashboards combining all business data

⚡ Performance & Enterprise Features

• 🚀 High-performance caching: Source-specific intelligent caching with TTL support

• 🔒 Enterprise security: Read-only access with query validation and connection timeouts

• 🏗️ Architecture detection: Automatic identification of star schemas and data warehouse patterns

• 🔧 Connection pooling: Efficient connection management across multiple business systems

• 🚀 Smithery deployment: Easy deployment with configuration UI on Smithery.ai

• MySQL 5.5+ compatible: Works with MySQL 5.5 and later versions

Quick Start

Option 1: Direct Install from GitHub

# Clone and install
git clone https://github.com/ttpears/mcp-mysql.git
cd mcp-mysql
npm install && npm run build

# Add to Claude Code with your MySQL credentials
# For server-wide access (recommended):
claude mcp add mysql-server npm start \
  -e MYSQL_HOST=localhost \
  -e MYSQL_USER=your_user \
  -e MYSQL_PASSWORD=your_password

# For single database access:
claude mcp add mysql-server npm start \
  -e MYSQL_HOST=localhost \
  -e MYSQL_USER=your_user \
  -e MYSQL_PASSWORD=your_password \
  -e MYSQL_DATABASE=your_database

Option 2: Deploy on Smithery.ai (Recommended)

Visit Smithery.ai MySQL MCP Server and click "Deploy" for easy setup with configuration UI.

Features when deployed on Smithery:

• 🎛️ Configuration UI: Easy setup with form-based configuration

• 🔄 Auto-updates: Automatic updates when new versions are released

• ⚡ High performance: Optimized deployment with caching enabled

• 🔒 Secure: Environment-based secret management

Option 3: Manual Installation

npm install mysql-mcp-server

Configuration

Environment Variables

Default Data Source

Multi-Source Data Federation

For additional business system data sources, use pattern: MYSQL_HOST_<SOURCE>_*

Note: Each additional data source requires at least MYSQL_HOST_<SOURCE>_HOST and MYSQL_HOST_<SOURCE>_PASSWORD to be configured.

Caching Configuration

Configuration Examples

Enterprise data federation setup:

# Default data source (backward compatible)
export MYSQL_HOST=localhost
export MYSQL_PORT=3306
export MYSQL_USER=analytics_user
export MYSQL_PASSWORD=your_password
export MYSQL_SSL=true
export MCP_MYSQL_CACHE_ENABLED=true

# CRM System (Salesforce MySQL backend)
export MYSQL_HOST_CRM_HOST=crm-db.company.com
export MYSQL_HOST_CRM_USER=crm_readonly
export MYSQL_HOST_CRM_PASSWORD=crm_secret
export MYSQL_HOST_CRM_DATABASE=salesforce_sync
export MYSQL_HOST_CRM_SSL=true

# E-commerce Platform (Shopify/WooCommerce)
export MYSQL_HOST_ECOMMERCE_HOST=shop-db.company.com
export MYSQL_HOST_ECOMMERCE_USER=ecommerce_analytics
export MYSQL_HOST_ECOMMERCE_PASSWORD=shop_secret
export MYSQL_HOST_ECOMMERCE_DATABASE=store_analytics

# ERP System (SAP/Oracle MySQL interface)
export MYSQL_HOST_ERP_HOST=erp-mysql.company.com
export MYSQL_HOST_ERP_USER=erp_reporting
export MYSQL_HOST_ERP_PASSWORD=erp_secret

# Marketing & Support Systems
export MYSQL_HOST_MARKETING_HOST=marketing-db.company.com
export MYSQL_HOST_MARKETING_USER=marketing_readonly
export MYSQL_HOST_MARKETING_PASSWORD=marketing_secret

export MYSQL_HOST_SUPPORT_HOST=support-db.company.com
export MYSQL_HOST_SUPPORT_USER=support_analytics
export MYSQL_HOST_SUPPORT_PASSWORD=support_secret

Single database access (legacy mode):

export MYSQL_HOST=localhost
export MYSQL_PORT=3306
export MYSQL_USER=readonly_user
export MYSQL_PASSWORD=your_password
export MYSQL_DATABASE=your_database
export MYSQL_SSL=true

Custom caching configuration:

export MCP_MYSQL_CACHE_ENABLED=true
export MCP_MYSQL_CACHE_DIR=/custom/cache/path
export MCP_MYSQL_CACHE_MAX_SIZE=104857600  # 100MB
export MCP_MYSQL_CACHE_RETENTION_DAYS=7    # 1 week

Usage

Running the Server

npm start

Available Tools

mysql_inventory

🏢 START HERE - Get comprehensive inventory of all configured business systems and their databases.

Parameters:

• refresh (boolean, optional): Force refresh of data source inventory

• host (string, optional): Get inventory for specific data source only

Examples:

// Get complete enterprise data source inventory
{}

// Refresh and get inventory for specific source
{
  "host": "crm",
  "refresh": true
}

What you get:

• 🏢 Business system classification (CRM, E-commerce, ERP, Marketing, Support, etc.)

• 📊 Database inventory with record counts and connection health

• 🔗 Federation capabilities and shared identifiers across systems

• 💡 Cross-system analysis recommendations

mysql_cross_host_query

🚀 ENTERPRISE POWER TOOL - Execute federated queries across multiple business systems.

Parameters:

• queries (array, required): Array of queries to execute across different data sources

  • host (string, required): Data source name to execute query on

  • database (string, optional): Database name within the data source

  • query (string, required): SQL query to execute

  • alias (string, optional): Alias for this query result

• combine_strategy (string, optional): How to combine results ('separate', 'union', 'comparison', 'correlation')

• analysis_focus (string, optional): Focus area ('performance', 'data_consistency', 'user_behavior', 'business_metrics')

Example - 360° Customer Intelligence:

{
  "queries": [
    {
      "host": "crm",
      "query": "SELECT customer_id, email, lead_source FROM customers WHERE status = 'active'",
      "alias": "crm_customers"
    },
    {
      "host": "ecommerce",
      "query": "SELECT customer_email as email, SUM(order_total) as lifetime_value FROM orders GROUP BY customer_email",
      "alias": "purchase_history"
    },
    {
      "host": "support",
      "query": "SELECT requester_email as email, COUNT(*) as ticket_count FROM tickets GROUP BY requester_email",
      "alias": "support_interactions"
    }
  ],
  "combine_strategy": "correlation",
  "analysis_focus": "user_behavior"
}

mysql_query

Execute read-only SQL queries against specific data sources.

Parameters:

• query (string, required): SQL query to execute

• params (array, optional): Parameters for prepared statements

• database (string, optional): Database name to connect to

• host (string, optional): Data source name (defaults to 'default')

Examples:

// Query default data source
{
  "query": "SELECT * FROM users WHERE status = ?",
  "params": ["active"]
}

// Query specific business system
{
  "host": "crm",
  "database": "salesforce_sync",
  "query": "SELECT COUNT(*) as total_leads FROM leads WHERE created_date >= '2024-01-01'"
}

mysql_schema

Get comprehensive schema information including relationships, constraints, and data patterns.

Parameters:

• table (string, optional): Specific table name to analyze

• include_relationships (boolean, default: true): Include foreign key relationships

• include_sample_data (boolean, default: false): Include sample data and statistics

• sample_size (number, default: 100, max: 1000): Number of sample rows to analyze

Examples:

// Get database overview with relationships
{}

// Get detailed table analysis with sample data
{
  "table": "users",
  "include_sample_data": true,
  "sample_size": 50
}

// Get basic table schema without relationships
{
  "table": "orders",
  "include_relationships": false
}

mysql_analyze_tables

Analyze table relationships and suggest optimal query patterns for user behavior analysis.

Parameters:

• tables (array, required): List of table names to analyze

• analysis_type (string, optional): Type of analysis ('relationships', 'user_behavior', 'data_flow')

Examples:

// Analyze table relationships
{
  "tables": ["users", "orders", "products"],
  "analysis_type": "relationships"
}

// Analyze for user behavior patterns
{
  "tables": ["users", "events", "sessions"],
  "analysis_type": "user_behavior"
}

// Trace data flow between tables
{
  "tables": ["users", "orders", "order_items"],
  "analysis_type": "data_flow"
}

mysql_discover_analytics

🚀 START HERE - Intelligently discover and analyze your entire MySQL server with expert data analytics insights and intelligent caching.

Parameters:

• databases (array, optional): List of databases to analyze (if not specified, discovers all accessible databases)

• focus_area (string, optional): Analytics focus ('user_behavior', 'sales_analytics', 'engagement', 'general')

• include_recommendations (boolean, default: true): Include expert query recommendations

• cross_database_analysis (boolean, default: true): Analyze relationships across databases

• detail_level (string, optional): Level of analysis ('summary', 'detailed', 'full')

• max_tables_per_db (number, default: 20): Maximum tables to analyze per database

• page (number, default: 1): Page number for pagination

• page_size (number, default: 5): Number of databases per page

Examples:

// Discover entire MySQL server for user behavior analysis
{
  "focus_area": "user_behavior",
  "cross_database_analysis": true
}

// Analyze specific databases only
{
  "databases": ["ecommerce", "analytics", "logs"],
  "focus_area": "sales_analytics"
}

// Quick server overview
{
  "focus_area": "general"
}

What you get:

• 🌐 Complete multi-database server analysis with all executed SQL queries shown

• 🧠 Intelligent table classification across all databases (fact tables, dimension tables, user tables, event tables)

• 🔄 Cross-database relationship mapping and pattern detection

• 📊 Expert analytics insights and performance recommendations per database

• 📈 Ready-to-use SQL queries for cross-database analytics patterns

• 🔍 Data quality assessments and optimization suggestions

• 🏗️ Architecture analysis (star schema detection, data warehouse patterns)

• ⚡ High-performance caching: All results cached with TTL for faster subsequent queries

• 📄 Pagination support: Handle large servers with configurable page sizes

🚀 Intelligent Caching System

The server includes a comprehensive caching system that dramatically improves performance for repeated operations:

Cache Types & TTL

• Query Results: 1-hour TTL - ~/.mcp-mysql-cache/queries/[date]/

• Schema Analysis: 1-2 hour TTL - ~/.mcp-mysql-cache/schema-snapshots/

• Discovery Reports: 4-hour TTL - ~/.mcp-mysql-cache/reports/discovery-reports/

• Relationship Analysis: Cached - ~/.mcp-mysql-cache/reports/relationship-analysis/

Cache Features

• Automatic TTL management: Expired cache automatically detected and refreshed

• Intelligent key generation: Complex queries cached with hash-based keys

• Size limits: Configurable maximum file size (default: 50MB)

• Storage organization: Organized by date and operation type

• Cache info: All responses include cache hit/miss information

• Cross-session: Cache persists across server restarts

Cache Benefits

• Faster repeated queries: Instant responses for cached operations

• Reduced database load: Less strain on your MySQL server

• Improved UX: Near-instantaneous results for complex analytics

• Development efficiency: Quick iterations during data exploration

Security Features

• Query Validation: Only read-only operations allowed (SELECT, SHOW, DESCRIBE, EXPLAIN)

• Length Limits: Queries limited to 10,000 characters

• Prepared Statements: Parameterized queries to prevent SQL injection

• Connection Timeouts: Configurable timeouts to prevent hanging connections

• Error Handling: Comprehensive error catching and logging

Database User Setup

For security, create a dedicated read-only MySQL user:

-- Create read-only user
CREATE USER 'readonly_user'@'%' IDENTIFIED BY 'secure_password';

-- Grant SELECT privileges
GRANT SELECT ON your_database.* TO 'readonly_user'@'%';

-- Grant SHOW privileges for schema inspection
GRANT SHOW VIEW ON your_database.* TO 'readonly_user'@'%';

-- Flush privileges
FLUSH PRIVILEGES;

Development

# Install dependencies
npm install

# Run in development mode
npm run dev

# Build for production
npm run build

Compatibility

• MySQL 5.5+

• MariaDB 10.0+

• Node.js 18+

Error Handling

The server provides detailed error messages for:

• Connection failures

• Invalid queries

• Query execution errors

• Parameter validation errors

All errors are logged to stderr while maintaining MCP protocol compliance.

Deployment

GitHub

git add .
git commit -m "Initial release of intelligent MySQL MCP Server"
git push origin main

Smithery.ai Registry

1. Ensure mcp.json is properly configured

2. Push to GitHub repository

3. Submit to Smithery.ai MCP Registry

4. Include the mcp.json file for automatic discovery

Contributing

1. Fork the repository

2. Create a feature branch (git checkout -b feature/amazing-feature)

3. Commit your changes (git commit -m 'Add amazing feature')

4. Push to the branch (git push origin feature/amazing-feature)

5. Open a Pull Request

License

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

Support

• 🐛 Issues: GitHub Issues

• 💬 Discussions: GitHub Discussions

• 📚 Documentation: Full Documentation