Skip to main content
Glama
designcomputer

MySQL MCP Server

execute_sql

Execute SQL queries on a MySQL server through a controlled interface for safe database exploration and data manipulation.

Instructions

Execute an SQL query on the MySQL server

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe SQL query to execute

Implementation Reference

  • Registers the 'execute_sql' tool using the @app.list_tools() decorator, defining its name, description, and input schema requiring a 'query' string parameter.
    @app.list_tools()
    async def list_tools() -> list[Tool]:
        """List available MySQL tools."""
        logger.info("Listing tools...")
        return [
            Tool(
                name="execute_sql",
                description="Execute an SQL query on the MySQL server",
                inputSchema={
                    "type": "object",
                    "properties": {
                        "query": {
                            "type": "string",
                            "description": "The SQL query to execute"
                        }
                    },
                    "required": ["query"]
                }
            )
        ]
  • Defines the input schema for 'execute_sql': an object with a required 'query' string property.
    inputSchema={
        "type": "object",
        "properties": {
            "query": {
                "type": "string",
                "description": "The SQL query to execute"
            }
        },
        "required": ["query"]
    }
  • The call_tool handler that executes SQL queries. It extracts the query argument, connects to MySQL, executes the query, and handles SHOW TABLES specially, SELECT-like queries with result sets, and non-SELECT queries (committing and returning affected row count).
    @app.call_tool()
    async def call_tool(name: str, arguments: dict) -> list[TextContent]:
        """Execute SQL commands."""
        config = get_db_config()
        logger.info(f"Calling tool: {name} with arguments: {arguments}")
    
        if name != "execute_sql":
            raise ValueError(f"Unknown tool: {name}")
    
        query = arguments.get("query")
        if not query:
            raise ValueError("Query is required")
    
        try:
            logger.info(f"Connecting to MySQL with charset: {config.get('charset')}, collation: {config.get('collation')}")
            with connect(**config) as conn:
                logger.info(f"Successfully connected to MySQL server version: {conn.get_server_info()}")
                with conn.cursor() as cursor:
                    cursor.execute(query)
    
                    # Special handling for SHOW TABLES
                    if query.strip().upper().startswith("SHOW TABLES"):
                        tables = cursor.fetchall()
                        result = ["Tables_in_" + config["database"]]  # Header
                        result.extend([table[0] for table in tables])
                        return [TextContent(type="text", text="\n".join(result))]
    
                    # Handle all other queries that return result sets (SELECT, SHOW, DESCRIBE etc.)
                    elif cursor.description is not None:
                        columns = [desc[0] for desc in cursor.description]
                        try:
                            rows = cursor.fetchall()
                            result = [",".join(map(str, row)) for row in rows]
                            return [TextContent(type="text", text="\n".join([",".join(columns)] + result))]
                        except Error as e:
                            logger.warning(f"Error fetching results: {str(e)}")
                            return [TextContent(type="text", text=f"Query executed but error fetching results: {str(e)}")]
    
                    # Non-SELECT queries
                    else:
                        conn.commit()
                        return [TextContent(type="text", text=f"Query executed successfully. Rows affected: {cursor.rowcount}")]
    
        except Error as e:
            logger.error(f"Error executing SQL '{query}': {e}")
            logger.error(f"Error code: {e.errno}, SQL state: {e.sqlstate}")
            return [TextContent(type="text", text=f"Error executing query: {str(e)}")]
  • Helper function get_db_config() reads database configuration from environment variables (MYSQL_HOST, MYSQL_PORT, MYSQL_USER, MYSQL_PASSWORD, MYSQL_DATABASE, etc.) used by the execute_sql handler.
    def get_db_config():
        """Get database configuration from environment variables."""
        config = {
            "host": os.getenv("MYSQL_HOST", "localhost"),
            "port": int(os.getenv("MYSQL_PORT", "3306")),
            "user": os.getenv("MYSQL_USER"),
            "password": os.getenv("MYSQL_PASSWORD"),
            "database": os.getenv("MYSQL_DATABASE"),
            # Add charset and collation to avoid utf8mb4_0900_ai_ci issues with older MySQL versions
            # These can be overridden via environment variables for specific MySQL versions
            "charset": os.getenv("MYSQL_CHARSET", "utf8mb4"),
            "collation": os.getenv("MYSQL_COLLATION", "utf8mb4_unicode_ci"),
            # Disable autocommit for better transaction control
            "autocommit": True,
            # Set SQL mode for better compatibility - can be overridden
            "sql_mode": os.getenv("MYSQL_SQL_MODE", "TRADITIONAL")
        }
    
        # Remove None values to let MySQL connector use defaults if not specified
        config = {k: v for k, v in config.items() if v is not None}
    
        if not all([config.get("user"), config.get("password"), config.get("database")]):
            logger.error("Missing required database configuration. Please check environment variables:")
            logger.error("MYSQL_USER, MYSQL_PASSWORD, and MYSQL_DATABASE are required")
            raise ValueError("Missing required database configuration")
    
        return config
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must fully disclose behavior. It fails to mention that executing SQL can be destructive (e.g., DROP, DELETE), requires authentication, or may have side effects. The agent is left unaware of potential risks.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, concise and direct. However, it could be more informative without sacrificing brevity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of an output schema, the description should explain the return value (e.g., result set, affected rows). It does not, leaving the agent without expectations. Also, no mention of safety precautions or supported SQL operations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% coverage with a description for the 'query' parameter. The tool description adds no extra meaning beyond the schema, so baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Execute' and the resource 'SQL query on the MySQL server'. It is specific enough to understand the basic action, but lacks differentiation from potential sibling tools (none exist here).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No usage guidelines are provided. The description does not specify when to use this tool versus others (though no siblings exist), nor does it mention prerequisites, constraints, or best practices.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/designcomputer/mysql_mcp_server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server