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Malove86

MCP MySQL Server

by Malove86

query

Run SELECT queries on MySQL databases using a standardized interface with MCP MySQL Server. Input SQL statements and optional parameters to retrieve database data efficiently.

Instructions

Execute a SELECT query

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsNoQuery parameters (optional)
sqlYesSQL SELECT query

Implementation Reference

  • The handler function for the 'query' tool. Ensures database connection, validates the SQL query (must be SELECT and pass security checks), executes it using the MySQL connection pool, and returns the results as a formatted JSON string.
    private async handleQuery(requestId: string, args: any) {
      await this.ensureConnection();
    
      if (!args.sql) {
        throw new McpError(ErrorCode.InvalidParams, 'SQL query is required');
      }
    
      if (!args.sql.trim().toUpperCase().startsWith('SELECT')) {
        throw new McpError(
          ErrorCode.InvalidParams,
          'Only SELECT queries are allowed with query tool'
        );
      }
    
      const sql = args.sql.trim();
    
      // 验证SQL安全性
      if (!validateSqlQuery(sql)) {
        throw new McpError(
          ErrorCode.InvalidParams,
          'SQL query contains potentially dangerous patterns'
        );
      }
    
      try {
        console.error(`[${requestId}] Executing query: ${sql.substring(0, 100)}${sql.length > 100 ? '...' : ''}`);
        const [rows] = await this.pool!.query(args.sql, args.params || []);
    
        // 计算结果集大小
        const resultSize = JSON.stringify(rows).length;
        console.error(`[${requestId}] Query executed successfully, result size: ${resultSize} bytes`);
    
        return {
          content: [
            {
              type: 'text',
              text: JSON.stringify(rows, null, 2),
            },
          ],
        };
      } catch (error) {
        const errorMsg = getErrorMessage(error);
        console.error(`[${requestId}] Query execution failed: ${errorMsg}`);
        throw new McpError(
          ErrorCode.InternalError,
          `Query execution failed: ${errorMsg}`
        );
      }
    }
  • The input schema definition for the 'query' tool, specifying 'sql' as required string and optional 'params' array.
    inputSchema: {
      type: 'object',
      properties: {
        sql: {
          type: 'string',
          description: 'SQL SELECT query',
        },
        params: {
          type: 'array',
          items: {
            type: ['string', 'number', 'boolean', 'null'],
          },
          description: 'Query parameters (optional)',
        },
      },
      required: ['sql'],
    },
  • src/index.ts:215-235 (registration)
    The tool registration in the ListTools response, defining name, description, and input schema for 'query'.
    {
      name: 'query',
      description: 'Execute a SELECT query',
      inputSchema: {
        type: 'object',
        properties: {
          sql: {
            type: 'string',
            description: 'SQL SELECT query',
          },
          params: {
            type: 'array',
            items: {
              type: ['string', 'number', 'boolean', 'null'],
            },
            description: 'Query parameters (optional)',
          },
        },
        required: ['sql'],
      },
    },
  • src/index.ts:293-295 (registration)
    The dispatch/registration in the CallToolRequestHandler switch statement that routes 'query' calls to the handleQuery function.
    case 'query':
      result = await this.handleQuery(requestId, request.params.arguments);
      break;
  • Helper function to validate SQL query for basic security by checking against dangerous patterns like DROP, DELETE, UNION SELECT, etc.
    // Helper to validate SQL query for basic security
    function validateSqlQuery(sql: string): boolean {
      // 检查是否存在常见SQL注入模式
      const dangerousPatterns = [
        /;\s*DROP\s+/i,
        /;\s*DELETE\s+/i,
        /;\s*UPDATE\s+/i,
        /;\s*INSERT\s+/i,
        /UNION\s+SELECT/i,
        /--/,
        /\/\*/,
        /xp_cmdshell/i
      ];
    
      return !dangerousPatterns.some(pattern => pattern.test(sql));
    }
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. 'Execute a SELECT query' implies a read-only operation, but it doesn't specify permissions required, potential side effects (e.g., read locks), rate limits, or error handling. This is a significant gap for a database query tool with zero annotation coverage.

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 waste. It's appropriately sized and front-loaded, clearly stating the core action 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?

Given the complexity of database queries and the lack of annotations and output schema, the description is incomplete. It doesn't address return values, error cases, or behavioral traits, which are crucial for an agent to use this tool effectively 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?

The schema description coverage is 100%, so the input schema already documents both parameters (sql and params) adequately. The description doesn't add any meaning beyond what the schema provides, such as SQL dialect or param usage examples. Baseline 3 is appropriate when the schema does the heavy lifting.

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 'Execute a SELECT query' clearly states the verb ('Execute') and resource ('SELECT query'), making the purpose understandable. However, it doesn't differentiate from potential siblings like 'describe_table' or 'list_tables' that might also involve database operations, so it's not fully specific about when to use this versus those alternatives.

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 the sibling tools (connect_db, describe_table, list_tables). It doesn't mention alternatives, prerequisites, or exclusions, leaving the agent to infer usage context from the tool name alone.

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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