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MySQL MCP Server

execute_sql

Execute SQL queries on a MySQL database to retrieve, insert, update, or delete data through a controlled interface.

Instructions

Execute an SQL query on the MySQL server

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe SQL query to execute

Implementation Reference

  • The call_tool handler function that implements the execute_sql tool. It validates the tool name, extracts the SQL query, connects to MySQL, executes the query, handles results for SELECT/SHOW queries or reports rowcount for modifications, with special case for SHOW TABLES.
    @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)}")]
  • Input schema definition for the execute_sql tool, specifying an object with a required 'query' property of type string.
    inputSchema={
        "type": "object",
        "properties": {
            "query": {
                "type": "string",
                "description": "The SQL query to execute"
            }
        },
        "required": ["query"]
    }
  • Registration of the execute_sql tool via the list_tools decorator, defining its name, description, and input schema.
    @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"]
                }
            )
        ]
  • Helper function get_db_config() used by the handler to obtain MySQL connection parameters from environment variables.
    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 provided, the description carries full burden for behavioral disclosure. It mentions execution but doesn't cover critical aspects like whether this is read-only vs. destructive, authentication requirements, transaction handling, error behavior, or result format. This leaves significant gaps for a database query tool.

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

Conciseness5/5

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

The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a tool with one parameter and gets straight to the point without unnecessary elaboration.

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?

For a database execution tool with no annotations and no output schema, the description is insufficient. It doesn't address behavioral traits, result format, error handling, or safety considerations that are crucial for proper tool invocation in a database context.

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?

Schema description coverage is 100%, so the schema already documents the single 'query' parameter. The description doesn't add any meaningful parameter semantics beyond what's in the schema, such as query syntax examples, supported SQL dialects, or size limitations.

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 action ('Execute') and target resource ('SQL query on the MySQL server'), providing a specific verb+resource combination. However, with no sibling tools mentioned, there's no opportunity to differentiate from alternatives, preventing a perfect score.

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?

The description provides no guidance on when to use this tool versus alternatives, prerequisites, or constraints. It simply states what the tool does without contextual usage information.

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

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