# Hugging Face Hub Search

> Use this tool when you need to discover relevant machine learning models and datasets through natural language queries or find alternatives to existing resources. It solves problems of semantic search, similarity-based discovery, and content retrieval, taking in natural language descriptions and outputting related models and datasets with detailed metadata. It is particularly useful for researchers and developers who want to go beyond keyword matching and leverage intelligent search capabilities with filtering options.

Canonical page: https://skillsregistry.net/skills/davanstrien-huggingface-hub-search  
JSON: https://api.skillsregistry.net/v1/skills/davanstrien-huggingface-hub-search

## Description

This MCP server provides AI-powered semantic search capabilities for Hugging Face models and datasets, built by Daniel van Strien from Hugging Face using a custom search API hosted on Hugging Face Spaces. It offers tools for semantic similarity search that goes beyond keyword matching to find models and datasets based on natural language descriptions, similarity-based discovery to find related resources, trending content retrieval with filtering options, and detailed metadata extraction including safetensors parsing for model architecture analysis and README card downloads. The implementation uses vector embeddings for intelligent search rather than simple text matching, supports parameter count filtering for models, and provides comprehensive filtering options by likes, downloads, and other metrics, making it valuable for researchers and developers who need to discover relevant ML resources through natural language queries or find alternatives to existing models and datasets.

## Trust

- **Trust score (0–1):** 0.64
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-02

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/davanstrien-huggingface-hub-search)
- **Repository:** <https://github.com/davanstrien/hub-semantic-search-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "davanstrien-huggingface-hub-search"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/davanstrien-huggingface-hub-search` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/davanstrien-huggingface-hub-search/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt