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Powerdrill MCP Server

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by powerdrillai

mcp_powerdrill_create_dataset

Create datasets for AI-powered data analysis in Powerdrill by specifying names and descriptions to organize information for smart insights.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesThe dataset name, which can be up to 128 characters in length
descriptionNoThe dataset description, which can be up to 128 characters in length

Implementation Reference

  • The complete handler function for the mcp_powerdrill_create_dataset tool, including input schema validation with Zod, client initialization, API call to createDataset, response handling, and error management.
    server.tool(
      'mcp_powerdrill_create_dataset',
      {
        name: z.string().describe('The dataset name, which can be up to 128 characters in length'),
        description: z.string().optional().describe('The dataset description, which can be up to 128 characters in length')
      },
      async (args, extra) => {
        try {
          const { name, description } = args;
    
          // Initialize Powerdrill client
          const client = new (await import('./utils/powerdrillClient.js')).PowerdrillClient();
    
          // Create dataset parameters
          const datasetParams = {
            name,
            description
          };
    
          // Create dataset
          const response = await client.createDataset(datasetParams);
    
          // Check if response is valid
          if (response.code !== 0 || !response.data) {
            throw new Error(`Invalid API response: ${JSON.stringify(response)}`);
          }
    
          // Format the response as MCP content
          return {
            content: [
              {
                type: "text",
                text: JSON.stringify({
                  id: response.data.id,
                  message: "Dataset created successfully"
                }, null, 2)
              }
            ]
          };
        } catch (error: any) {
          console.error(`Error creating dataset: ${error.message}`);
    
          // Return error response
          return {
            content: [
              {
                type: "text",
                text: JSON.stringify({
                  error: `Error creating dataset: ${error.message}`,
                  errorType: error.name,
                  errorStack: process.env.NODE_ENV === 'development' ? error.stack : undefined
                }, null, 2)
              }
            ],
            isError: true
          };
        }
      }
    );
  • Supporting utility in PowerdrillClient class that sends the POST request to the Powerdrill API /datasets endpoint to create the dataset.
    async createDataset(params: CreateDatasetParams) {
      try {
        // Include user_id in the request body if not provided
        const requestBody = {
          ...params,
          user_id: params.user_id || this.config.userId
        };
    
        const response = await this.client.post('/datasets', requestBody);
        return response.data;
      } catch (error: any) {
        console.error('Error creating dataset:', error.message);
        throw error;
      }
    }
  • TypeScript interface defining the input parameters for the createDataset method (name required, description and user_id optional).
    export interface CreateDatasetParams {
      name: string;
      description?: string;
      user_id?: string;
    }
  • src/index.ts:543-543 (registration)
    Tool registration call using McpServer.tool method, specifying the tool name 'mcp_powerdrill_create_dataset'.
    server.tool(
  • Zod schema for the tool's input parameters used in MCP server registration.
    {
      name: z.string().describe('The dataset name, which can be up to 128 characters in length'),
      description: z.string().optional().describe('The dataset description, which can be up to 128 characters in length')
    },
Behavior1/5

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

Tool has no description.

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

Conciseness1/5

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

Tool has no description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool has no description.

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?

Tool has no description.

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

Purpose1/5

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

Tool has no description.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Tool has no description.

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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