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MCP-MongoDB-MySQL-Server

query

Execute SQL SELECT queries to retrieve data from MySQL and MongoDB databases through a standardized interface, supporting query parameters for dynamic operations.

Instructions

Execute a SELECT query

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sqlYesSQL SELECT query
paramsNoQuery parameters (optional)

Implementation Reference

  • The handler function that executes SELECT SQL queries on the MySQL database using the provided SQL and optional parameters. Ensures connection, validates SELECT only, executes query, and returns JSON results.
    private async handleQuery(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'
        );
      }
    
      try {
        const [rows] = await this.connection!.query(args.sql, args.params || []);
        return {
          content: [
            {
              type: 'text',
              text: JSON.stringify(rows, null, 2),
            },
          ],
        };
      } catch (error) {
        throw new McpError(
          ErrorCode.InternalError,
          `Query execution failed: ${getErrorMessage(error)}`
        );
      }
    }
  • Input schema definition for the 'query' tool, specifying required 'sql' 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:259-279 (registration)
    Tool registration in the listTools response, including name, description, and inputSchema for the 'query' tool.
    {
      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:539-540 (registration)
    Dispatch case in CallToolRequestSchema handler that routes 'query' tool calls to the handleQuery method.
    case 'query':
      return await this.handleQuery(request.params.arguments);

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations, the description bears full responsibility for behavioral disclosure. It only states the tool executes a SELECT query, but does not explicitly confirm it is read-only, mention permission requirements, error handling, or the effect of malformed queries. The implied read-only nature is not sufficient.

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 concise sentence that front-loads the main action. It is not verbose, though it could include more context without losing conciseness. The structure is effective but minimal.

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?

There is no output schema, yet the description does not explain what the tool returns (e.g., result set structure, row count, error messages). It also lacks information on pagination, limits, or behavior with large queries, leaving the agent with significant gaps.

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 both parameters ('sql' and 'params') adequately. The description adds no additional meaning or context about parameter usage, formatting, or constraints beyond the schema, earning a baseline score of 3.

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

Purpose5/5

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

The description 'Execute a SELECT query' clearly identifies the tool's action (execute) and resource (SELECT query). It distinguishes from sibling tools like 'execute' (which likely handles other SQL statements) and 'describe_table'/'list_tables' (which are informational).

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. It does not mention that for non-SELECT queries (e.g., INSERT, UPDATE) one should use the sibling 'execute' tool, nor does it specify any prerequisites or limitations.

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