Dataset Viewer MCP Server
About
Interact with the Hugging Face Dataset Viewer API to browse, filter, and get statistics for datasets.
Details
- Author
- privetin
- GitHub stars
- 31
- Downloads
- 383
- Categories
- Database, Other, Search
Jump to
- Uses dataset:// URI scheme for accessing Hugging Face datasets
- Supports dataset configurations and splits with pagination
- Handles authentication for private datasets via optional token
- Provides search and SQL-like filtering of dataset rows
- Offers dataset statistics and analysis tools
- Allows downloading entire datasets in Parquet format
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Dataset Viewer MCP ServerCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Install Python 3.12+ and uv, clone the repository, create a virtual environment, and install the package. Configure the server by setting the HUGGINGFACE_TOKEN environment variable for private datasets and adding the command to your MCP client configuration (e.g., Claude Desktop).
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"dataset viewer mcp server": {
"dataset-viewer": {
"command": "uv",
"args": [
"venv"
]
}
}
}
}McpServers
{
"dataset-viewer": {
"command": "uv",
"args": [
"venv"
]
}
}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
2. Create a virtual environment and install:
```bash
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