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cemalturkcan

MariaDB MCP Server

by cemalturkcan

describe_table

Retrieve column metadata for any MariaDB table to understand its structure, data types, and constraints.

Instructions

Returns column information for a table.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
connectionYes
tableYes
databaseNo

Implementation Reference

  • Schema definition for the 'describe_table' tool, including input properties (connection, table, database) and required fields (connection, table).
    {
      name: "describe_table",
      description: "Returns column information for a table.",
      inputSchema: {
        type: "object",
        properties: {
          connection: { type: "string", enum: readableConnections },
          table: { type: "string" },
          database: { type: "string" },
        },
        required: ["connection", "table"],
      },
  • Handler for the 'describe_table' tool. Extracts connection, table, and database; validates required fields; builds a DESCRIBE SQL query and executes it via db.runReadOnly.
    case "describe_table": {
      const { connection, table, database } = args || {};
      if (!connection) return fail("'connection' field is required.");
      if (!table) return fail("'table' field is required.");
      const path = database ? `\`${database}\`.\`${table}\`` : `\`${table}\``;
      const rows = await db.runReadOnly(connection, `DESCRIBE ${path}`);
      return ok(rows);
    }
  • src/index.js:31-37 (registration)
    Registration of the 'describe_table' tool via ListToolsRequestSchema handler. buildToolDefinitions (from tools.js) returns the tool list which includes describe_table.
    server.setRequestHandler(ListToolsRequestSchema, async () => ({
      tools: buildToolDefinitions(
        readableConnections,
        writableConnections,
        allConnections,
      ),
    }));
Behavior2/5

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

With no annotations, the description bears full responsibility for disclosing behavior. It only states the output is 'column information' without mentioning read-only nature, error handling, permissions, or side effects. This is insufficient for an agent to predict behavior.

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

Conciseness3/5

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

The description is a single sentence, which is concise and front-loaded. However, it is too minimal given the tool's complexity (3 parameters, no output schema). Brevity is not always conciseness; here it sacrifices clarity.

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 3 parameters, no output schema, and sibling tools, the description is incomplete. It fails to specify the output format, parameter constraints (e.g., which connections are valid), or how to handle missing parameters like database. An agent would have to guess or infer.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description adds no meaning to parameters. It doesn't explain what 'connection', 'table', or 'database' represent or how they interact, leaving the agent with only the raw schema (names and types) which is insufficient.

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 tool returns column information for a table, which is specific and distinguishes it from siblings like list_tables (which lists table names) and execute_select (which runs queries). The verb 'returns' and resource 'column information' are appropriate.

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 guidance on when to use this tool versus alternatives such as list_tables or suggest_query. It does not mention prerequisites, typical use cases, or which sibling tools might be more appropriate for different scenarios.

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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