mcp-dataset-curator

MCP server for dataset curation retainer - deduplication, rebalancing, and poison detection.

Tools

deduplicate_dataset

Remove duplicate entries from a dataset.

Parameters:

• dataset_id (string, required): Dataset identifier

• data (array, required): Dataset entries

• key_fields (array, required): Fields to use for deduplication

• keep (string, optional): "first" or "last" (default: "first")

rebalance_classes

Rebalance class distribution in a dataset.

Parameters:

• dataset_id (string, required): Dataset identifier

• data (array, required): Dataset entries

• label_field (string, required): Field containing class labels

• target_distribution (object, optional): Target class distribution

• method (string, optional): "undersample", "oversample", or "smote" (default: "undersample")

remove_poisoned_entries

Detect and remove potentially poisoned/malicious entries.

Parameters:

• dataset_id (string, required): Dataset identifier

• data (array, required): Dataset entries

• detection_methods (array, optional): Detection methods - statistical_outlier, label_inconsistency, feature_anomaly, duplicate_label (default: all)

• threshold (number, optional): Confidence threshold for removal (default: 0.95)

Related MCP server: Structured Data Validator & Transformer MCP Server

Installation

pip install -r requirements.txt

Usage

python main.py

Connecting to Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "dataset-curator": {
      "command": "python",
      "args": ["/path/to/mcp-dataset-curator/main.py"],
      "cwd": "/path/to/mcp-dataset-curator"
    }
  }
}

License

MIT