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MCP Server MySQL

by nilsir

drop_index

Remove an index from a MySQL database table to optimize storage or modify table structure. Specify the table name and index to delete.

Instructions

Drop an index from a table

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableYesTable name
indexNameYesIndex name
databaseNoDatabase name (optional)

Implementation Reference

  • The asynchronous handler function that executes the logic to drop the specified index from the table using the database connection pool.
    async ({ table, indexName, database }) => {
      const p = await getPool();
    
      const tableName = database ? `\`${database}\`.\`${table}\`` : `\`${table}\``;
      await p.execute(`DROP INDEX \`${indexName}\` ON ${tableName}`);
    
      const output = {
        success: true,
        table,
        indexName,
        database: database || null,
      };
    
      return {
        content: [
          {
            type: "text" as const,
            text: `Index ${indexName} dropped from ${table}`,
          },
        ],
        structuredContent: output,
      };
    }
  • Zod schema defining the input parameters for the drop_index tool: table, indexName, and optional database.
    {
      table: z.string().describe("Table name"),
      indexName: z.string().describe("Index name"),
      database: z.string().optional().describe("Database name (optional)"),
    },
  • src/index.ts:563-595 (registration)
    The server.tool() call that registers the drop_index tool, including its name, description, input schema, and inline handler function.
    // Tool: drop_index
    server.tool(
      "drop_index",
      "Drop an index from a table",
      {
        table: z.string().describe("Table name"),
        indexName: z.string().describe("Index name"),
        database: z.string().optional().describe("Database name (optional)"),
      },
      async ({ table, indexName, database }) => {
        const p = await getPool();
    
        const tableName = database ? `\`${database}\`.\`${table}\`` : `\`${table}\``;
        await p.execute(`DROP INDEX \`${indexName}\` ON ${tableName}`);
    
        const output = {
          success: true,
          table,
          indexName,
          database: database || null,
        };
    
        return {
          content: [
            {
              type: "text" as const,
              text: `Index ${indexName} dropped from ${table}`,
            },
          ],
          structuredContent: output,
        };
      }
    );
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. 'Drop' implies a destructive operation, but it doesn't specify whether this requires specific permissions, is irreversible, affects database performance, or has side effects. This is inadequate for a mutation 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 wasted words. It's front-loaded with the core action and resource, making it immediately clear 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 destructive tool with no annotations and no output schema, the description is incomplete. It lacks critical context like success/failure behavior, return values, error conditions, or impact on database operations, leaving significant gaps for agent understanding.

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 all three parameters (table, indexName, database). The description adds no additional meaning beyond what the schema provides, such as parameter relationships or usage examples, meeting the baseline for high schema coverage.

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 ('drop') and resource ('index from a table'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'drop_table' or 'alter_table' which might also affect table structures, missing explicit sibling distinction.

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. There's no mention of prerequisites (e.g., index must exist), consequences (e.g., performance impact), or when to choose this over other tools like 'alter_table' for index modifications.

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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