Data · MODEL CONTEXT PROTOCOL

dataset-viewer

MCP server for Hugging Face dataset viewer

连接能力

dataset-viewer 为 AI Agent 提供什么

  • Uses `dataset://` URI scheme for accessing Hugging Face datasets
  • Supports dataset configurations and splits
  • Provides paginated access to dataset contents
  • Handles authentication for private datasets
  • Supports searching and filtering dataset contents
  • Provides dataset statistics and analysis
  • **validate**
  • Check if a dataset exists and is accessible
  • Parameters:
  • `dataset`: Dataset identifier (e.g. 'stanfordnlp/imdb')
  • `auth_token` (optional): For private datasets
  • **get_info**
  • Get detailed information about a dataset
  • Parameters:
  • `dataset`: Dataset identifier
  • `auth_token` (optional): For private datasets
  • **get_rows**
  • Get paginated contents of a dataset
  • Parameters:
  • `dataset`: Dataset identifier
  • `config`: Configuration name
  • `split`: Split name
  • `page` (optional): Page number (0-based)
  • `auth_token` (optional): For private datasets
  • **get_first_rows**
  • Get first rows from a dataset split
  • Parameters:
  • `dataset`: Dataset identifier
  • `config`: Configuration name
  • `split`: Split name
  • `auth_token` (optional): For private datasets
  • **get_statistics**
  • Get statistics about a dataset split
  • Parameters:
  • `dataset`: Dataset identifier
  • `config`: Configuration name
  • `split`: Split name
  • `auth_token` (optional): For private datasets
  • **search_dataset**
  • Search for text within a dataset
  • Parameters:
  • `dataset`: Dataset identifier
  • `config`: Configuration name
  • `split`: Split name
  • `query`: Text to search for
  • `auth_token` (optional): For private datasets
  • **filter**
  • Filter rows using SQL-like conditions
  • Parameters:
  • `dataset`: Dataset identifier
  • `config`: Configuration name
  • `split`: Split name
  • `where`: SQL WHERE clause (e.g. "score > 0.5")
  • `orderby` (optional): SQL ORDER BY clause
  • `page` (optional): Page number (0-based)
  • `auth_token` (optional): For private datasets
  • **get_parquet**
  • Download entire dataset in Parquet format
  • Parameters:
  • `dataset`: Dataset identifier
  • `auth_token` (optional): For private datasets
  • Python 3.12 or higher
  • [uv](https://github.com/astral-sh/uv) - Fast Python package installer and resolver
  • Clone the repository:
  • Create a virtual environment and install:
  • `HUGGINGFACE_TOKEN`: Your Hugging Face API token for accessing private datasets

安全

MCP 收录不等于安全审核

MCP 服务器可能获得模型上下文、凭据、本地文件或调用外部系统的权限。连接 Agent 前,请检查代码、环境变量、网络行为、软件包来源与维护状态。

README

仓库文档

Dataset Viewer MCP Server

An MCP server for interacting with the Hugging Face Dataset Viewer API, providing capabilities to browse and analyze datasets hosted on the Hugging Face Hub.

Features

Resources

  • Uses dataset:// URI scheme for accessing Hugging Face datasets
  • Supports dataset configurations and splits
  • Provides paginated access to dataset contents
  • Handles authentication for private datasets
  • Supports searching and filtering dataset contents
  • Provides dataset statistics and analysis

Tools

The server provides the following tools:

  1. validate

    • Check if a dataset exists and is accessible
    • Parameters:
      • dataset: Dataset identifier (e.g. 'stanfordnlp/imdb')
      • auth_token (optional): For private datasets
  2. get_info

    • Get detailed information about a dataset
    • Parameters:
      • dataset: Dataset identifier
      • auth_token (optional): For private datasets
  3. get_rows

    • Get paginated contents of a dataset
    • Parameters:
      • dataset: Dataset identifier
      • config: Configuration name
      • split: Split name
      • page (optional): Page number (0-based)
      • auth_token (optional): For private datasets
  4. get_first_rows

    • Get first rows from a dataset split
    • Parameters:
      • dataset: Dataset identifier
      • config: Configuration name
      • split: Split name
      • auth_token (optional): For private datasets
  5. get_statistics

    • Get statistics about a dataset split
    • Parameters:
      • dataset: Dataset identifier
      • config: Configuration name
      • split: Split name
      • auth_token (optional): For private datasets
  6. search_dataset

    • Search for text within a dataset
    • Parameters:
      • dataset: Dataset identifier
      • config: Configuration name
      • split: Split name
      • query: Text to search for
      • auth_token (optional): For private datasets
  7. filter

    • Filter rows using SQL-like conditions
    • Parameters:
      • dataset: Dataset identifier
      • config: Configuration name
      • split: Split name
      • where: SQL WHERE clause (e.g. "score > 0.5")
      • orderby (optional): SQL ORDER BY clause
      • page (optional): Page number (0-based)
      • auth_token (optional): For private datasets
  8. get_parquet

    • Download entire dataset in Parquet format
    • Parameters:
      • dataset: Dataset identifier
      • auth_token (optional): For private datasets

Installation

Prerequisites

  • Python 3.12 or higher
  • uv - Fast Python package installer and resolver

Setup

  1. Clone the repository:
git clone https://github.com/privetin/dataset-viewer.git
cd dataset-viewer
  1. Create a virtual environment and install:
# Create virtual environment
uv venv

# Activate virtual environment
# On Unix:
source .venv/bin/activate
# On Windows:
.venv\Scripts\activate

# Install in development mode
uv add -e .

Configuration

Environment Variables

  • HUGGINGFACE_TOKEN: Your Hugging Face API token for accessing private datasets

Claude Desktop Integration

Add the following to your Claude Desktop config file:

On Windows: %APPDATA%\Claude\claude_desktop_config.json

On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "dataset-viewer": {
      "command": "uv",
      "args": [
        "--directory",
        "parent_to_repo/dataset-viewer",
        "run",
        "dataset-viewer"
      ]
    }
  }
}

License

MIT License - see LICENSE for details

在 GitHub 查看 README

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