MySQL

Connect HolmesGPT to MySQL databases to analyze query performance, investigate slow queries, optimize indexes, examine database health, and read data for troubleshooting.

You can configure multiple MySQL instances with different names (e.g., orders-rds, analytics-mysql, staging-mysql).

Creating a Read-Only User

-- Create user
CREATE USER 'holmes_readonly'@'%' IDENTIFIED BY 'your_secure_password';

-- Grant read-only permissions
GRANT SELECT, SHOW VIEW, PROCESS ON *.* TO 'holmes_readonly'@'%';

-- Grant access to performance schema
GRANT SELECT ON performance_schema.* TO 'holmes_readonly'@'%';
GRANT SELECT ON information_schema.* TO 'holmes_readonly'@'%';

FLUSH PRIVILEGES;

For specific database only:

CREATE USER 'holmes_readonly'@'%' IDENTIFIED BY 'your_secure_password';
GRANT SELECT, SHOW VIEW ON your_database.* TO 'holmes_readonly'@'%';
GRANT SELECT ON performance_schema.* TO 'holmes_readonly'@'%';
GRANT SELECT ON information_schema.* TO 'holmes_readonly'@'%';
GRANT PROCESS ON *.* TO 'holmes_readonly'@'%';
FLUSH PRIVILEGES;

Configuration

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~/.holmes/config.yaml:

toolsets:
  orders-mysql:
    type: database
    config:
      connection_url: "mysql+pymysql://holmes_readonly:your_secure_password@mysql.example.com:3306/orders"
    llm_instructions: "Orders database with customer and product data"

  analytics-mysql:
    type: database
    config:
      connection_url: "mysql+pymysql://analyst:pass@analytics-mysql.internal:3306/analytics"
    llm_instructions: "Analytics database for reporting queries"

Using environment variables:

toolsets:
  orders-mysql:
    type: database
    config:
      connection_url: "{{ env.MYSQL_URL }}"

Connection URL format:

mysql+pymysql://[username]:[password]@[host]:[port]/[database]

Step 1: Create secret with credentials

kubectl create secret generic mysql-credentials \
  --from-literal=url='mysql+pymysql://holmes_readonly:your_secure_password@mysql.example.com:3306/orders' \
  -n holmes

Step 2: Configure in values.yaml

additionalEnvVars:
  - name: MYSQL_URL
    valueFrom:
      secretKeyRef:
        name: mysql-credentials
        key: url

toolsets:
  orders-mysql:
    type: database
    config:
      connection_url: "{{ env.MYSQL_URL }}"
    llm_instructions: "Orders database with customer and product data"

Multiple instances:

additionalEnvVars:
  - name: ORDERS_MYSQL_URL
    valueFrom:
      secretKeyRef:
        name: mysql-orders
        key: url
  - name: ANALYTICS_MYSQL_URL
    valueFrom:
      secretKeyRef:
        name: mysql-analytics
        key: url

toolsets:
  orders-mysql:
    type: database
    config:
      connection_url: "{{ env.ORDERS_MYSQL_URL }}"

  analytics-mysql:
    type: database
    config:
      connection_url: "{{ env.ANALYTICS_MYSQL_URL }}"

Step 1: Create secret with credentials

kubectl create secret generic mysql-credentials \
  --from-literal=url='mysql+pymysql://holmes_readonly:your_secure_password@mysql.example.com:3306/orders' \
  -n default

Step 2: Configure in values.yaml

holmes:
  additionalEnvVars:
    - name: MYSQL_URL
      valueFrom:
        secretKeyRef:
          name: mysql-credentials
          key: url

  toolsets:
    orders-mysql:
      type: database
      config:
        connection_url: "{{ env.MYSQL_URL }}"
      llm_instructions: "Orders database with customer and product data"

Multiple instances:

holmes:
  additionalEnvVars:
    - name: ORDERS_MYSQL_URL
      valueFrom:
        secretKeyRef:
          name: mysql-orders
          key: url
    - name: ANALYTICS_MYSQL_URL
      valueFrom:
        secretKeyRef:
          name: mysql-analytics
          key: url

  toolsets:
    orders-mysql:
      type: database
      config:
        connection_url: "{{ env.ORDERS_MYSQL_URL }}"

    analytics-mysql:
      type: database
      config:
        connection_url: "{{ env.ANALYTICS_MYSQL_URL }}"

Configuration Options

• connection_url (required): MySQL connection URL
• read_only (default: true): Only allow SELECT/SHOW/DESCRIBE/EXPLAIN/WITH statements
• verify_ssl (default: true): Verify SSL certificates
• max_rows (default: 200): Maximum rows to return (1-10000)
• llm_instructions: Context about this database

Common Use Cases

"Analyze slow query: SELECT * FROM orders WHERE created_at > '2024-01-01'"

"Show table structure for products and suggest indexes"

"What are the 10 largest tables?"

"Check for missing indexes on frequently queried columns"