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dkmaker

mcp-azure-tablestorage

list_tables

Retrieve and display all tables in an Azure Storage account, optionally filtering results by a provided prefix.

Instructions

List all tables in the storage account

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
prefixNoOptional prefix to filter table names

Implementation Reference

  • The core handler function for the 'list_tables' tool. It uses TableServiceClient to iterate over all tables, filters by optional 'prefix' argument, collects table names, and returns them as a JSON-formatted text response.
    private async handleListTables(args: ListTablesArgs) {
      const serviceClient = TableServiceClient.fromConnectionString(this.connectionString);
      const tables = [];
      const iterator = serviceClient.listTables();
      
      for await (const table of iterator) {
        if (table.name && (!args.prefix || table.name.startsWith(args.prefix))) {
          tables.push(table.name);
        }
      }
    
      return {
        content: [
          {
            type: 'text',
            text: JSON.stringify(tables, null, 2),
          },
        ],
      };
    }
  • src/index.ts:129-141 (registration)
    Tool registration in the ListToolsRequest handler, defining name, description, and input schema for 'list_tables'.
    {
      name: 'list_tables',
      description: 'List all tables in the storage account',
      inputSchema: {
        type: 'object',
        properties: {
          prefix: {
            type: 'string',
            description: 'Optional prefix to filter table names',
          },
        },
      },
    },
  • src/index.ts:167-169 (registration)
    Dispatch logic in CallToolRequest handler that routes 'list_tables' calls to the handleListTables function.
    case 'list_tables':
      const listArgs = request.params.arguments as ListTablesArgs;
      return await this.handleListTables(listArgs);
  • TypeScript interface defining the input parameters for the list_tables tool (optional prefix string). Used for type safety in handler and dispatch.
    interface ListTablesArgs {
      prefix?: string;
    }
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. It states the tool lists tables but doesn't mention any behavioral traits such as pagination, rate limits, authentication requirements, or what happens if no tables exist. This leaves significant gaps in understanding how the tool behaves operationally.

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 that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.

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 lack of annotations and output schema, the description is incomplete for a tool that interacts with storage resources. It doesn't address behavioral aspects like return format, error handling, or operational constraints, which are important for an agent to use the tool effectively in real scenarios.

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 input schema already documents the optional 'prefix' parameter. The description doesn't add any additional meaning about parameters beyond what's in the schema, such as format examples or usage context. The baseline score of 3 reflects adequate but minimal value added.

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 ('List') and target resource ('all tables in the storage account'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'get_table_schema' or 'query_table', which prevents a perfect score.

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 like 'get_table_schema' or 'query_table'. There's no mention of use cases, prerequisites, or exclusions, leaving the agent with minimal contextual direction.

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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