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wenjiachengy

MySQL MCP Server

by wenjiachengy

execute_sql

Execute SQL queries on MySQL databases to retrieve, modify, or analyze data through secure database interactions.

Instructions

Execute an SQL query on the MySQL server

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe SQL query to execute

Implementation Reference

  • The @app.call_tool() handler function that implements the logic for the 'execute_sql' tool, including SQL execution, result handling, and error management.
    @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:
            with connect(**config) as conn:
                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:
                        columns = [desc[0] for desc in cursor.description]
                        rows = cursor.fetchall()
                        result = [",".join(map(str, row)) for row in rows]
                        return [TextContent(type="text", text="\n".join([",".join(columns)] + result))]
                    
                    # 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}")
            return [TextContent(type="text", text=f"Error executing query: {str(e)}")]
  • The input schema definition for the 'execute_sql' tool, specifying the required 'query' parameter.
    inputSchema={
        "type": "object",
        "properties": {
            "query": {
                "type": "string",
                "description": "The SQL query to execute"
            }
        },
        "required": ["query"]
    }
  • The registration of the 'execute_sql' tool in the list_tools() function, including name, description, and schema.
    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"]
            }
        )
    ]

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
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.

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