load_dataset
Load datasets like german, compas, or adult for evaluating AI explanation methods through the OpenXAI MCP Server interface.
Instructions
Load a specific dataset from OpenXAI
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| dataset_name | Yes | Name of the dataset to load (e.g., german, compas, adult) | |
| download | No | Whether to download the dataset if not available locally |
Implementation Reference
- index.js:407-464 (handler)The primary handler function that executes the load_dataset tool. It retrieves dataset metadata for supported datasets (german, compas, adult), validates the dataset_name, and returns formatted information including dataset stats and a Python code example for loading the dataset using OpenXAI.
async loadDataset(datasetName, download = true) { const datasetInfo = { german: { description: 'German Credit dataset loaded successfully', features: 20, samples: 1000, classes: 2, task: 'classification' }, compas: { description: 'COMPAS Recidivism dataset loaded successfully', features: 11, samples: 6172, classes: 2, task: 'classification' }, adult: { description: 'Adult Income dataset loaded successfully', features: 14, samples: 48842, classes: 2, task: 'classification' } }; const info = datasetInfo[datasetName]; if (!info) { throw new Error(`Dataset '${datasetName}' not found. Available datasets: ${Object.keys(datasetInfo).join(', ')}`); } const codeExample = ` # Example usage with OpenXAI: from openxai.dataloader import ReturnLoaders # Load the dataset trainloader, testloader = ReturnLoaders(data_name='${datasetName}', download=${download}) # Get a sample from the test dataset inputs, labels = next(iter(testloader)) print(f"Input shape: {inputs.shape}") print(f"Labels shape: {labels.shape}") `; return { content: [ { type: 'text', text: `${info.description}\n\n` + `Dataset: ${datasetName}\n` + `Features: ${info.features}\n` + `Samples: ${info.samples}\n` + `Classes: ${info.classes}\n` + `Task: ${info.task}\n\n` + `Python code example:\n\`\`\`python${codeExample}\`\`\`` } ] }; } - index.js:56-70 (schema)Input schema definition for the load_dataset tool, specifying dataset_name as required string and optional download boolean.
inputSchema: { type: 'object', properties: { dataset_name: { type: 'string', description: 'Name of the dataset to load (e.g., german, compas, adult)', }, download: { type: 'boolean', description: 'Whether to download the dataset if not available locally', default: true } }, required: ['dataset_name'] } - index.js:53-71 (registration)Registration of the load_dataset tool in the MCP server's tool list, including name, description, and input schema.
{ name: 'load_dataset', description: 'Load a specific dataset from OpenXAI', inputSchema: { type: 'object', properties: { dataset_name: { type: 'string', description: 'Name of the dataset to load (e.g., german, compas, adult)', }, download: { type: 'boolean', description: 'Whether to download the dataset if not available locally', default: true } }, required: ['dataset_name'] } }, - index.js:258-259 (helper)Dispatch case in the CallToolRequestHandler that routes load_dataset calls to the loadDataset method.
case 'load_dataset': return await this.loadDataset(args.dataset_name, args.download);