router/mcp
H

Hugging Face

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by co.huggingface · HTTP

Hugging Face by co.huggingface — connect via http to access its tools through your RouterMCP gateway.

#registry.modelcontextprotocol.io
TOOLS
10
available on this server
TRANSPORT
HTTP
SSE fallback
AUTH
Varies
depends on server or gateway configuration
REGION
Global
multi-region ready
STATUS
Active
accepting connections

Overview

ATTACHREADY
routermcp.jsonjson
{
"mcpServers": {
"hf-mcp-server": {
"url": "https://huggingface.co/mcp?login",
"type": "http"
}
},
"requiresAuth": true,
"requiresOAuth": true
}

Tools (10)

hf_whoami

Hugging Face tools are being used by authenticated user 'rohanw3dev'

schema
{
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"properties": {}
}

space_search

Find Hugging Face Spaces using semantic search. IMPORTANT Only MCP Servers can be used with the dynamic_space toolInclude links to the Space when presenting the results.

schema
{
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"required": [
"query"
],
"properties": {
"mcp": {
"type": "boolean",
"default": false,
"description": "Only return MCP Server enabled Spaces"
},
"limit": {
"type": "number",
"default": 10,
"description": "Number of results to return"
},
"query": {
"type": "string",
"maxLength": 100,
"minLength": 1,
"description": "Semantic Search Query"
}
},
"additionalProperties": false
}

hub_repo_search

Search Hugging Face repositories with a shared query interface. You can target models, datasets, spaces, or aggregate across multiple repo types in one call. Use space_search for semantic-first discovery of Spaces. Include links to repositories in your response.

schema
{
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"properties": {
"sort": {
"enum": [
"trendingScore",
"downloads",
"likes",
"createdAt",
"lastModified"
],
"type": "string",
"description": "Sort order (descending): trendingScore, downloads, likes, createdAt, lastModified"
},
"limit": {
"type": "number",
"default": 20,
"maximum": 100,
"minimum": 1,
"description": "Maximum number of results to return per selected repo type"
},
"query": {
"type": "string",
"description": "Search term. Leave blank and specify sort + limit to browse trending or recent repositories."
},
"author": {
"type": "string",
"description": "Organization or user namespace to filter by (e.g. 'google', 'meta-llama', 'huggingface')."
},
"filters": {
"type": "array",
"items": {
"type": "string"
},
"description": "Optional hub filter tags. Applied to each selected repo type (e.g. [\"text-generation\"], [\"language:en\"], [\"mcp-server\"])."
},
"repo_types": {
"type": "array",
"items": {
"enum": [
"model",
"dataset",
"space"
],
"type": "string"
},
"default": [
"model",
"dataset"
],
"maxItems": 3,
"minItems": 1,
"description": "Repository types to search. Defaults to [\"model\", \"dataset\"]. space uses keyword search via /api/spaces."
}
},
"additionalProperties": false
}

paper_search

Find Machine Learning research papers on the Hugging Face hub. Include 'Link to paper' When presenting the results. Consider whether tabulating results matches user intent.

schema
{
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"required": [
"query"
],
"properties": {
"query": {
"type": "string",
"maxLength": 200,
"minLength": 3,
"description": "Semantic Search query"
},
"concise_only": {
"type": "boolean",
"default": false,
"description": "Return a 2 sentence summary of the abstract. Use for broad search terms which may return a lot of results. Check with User if unsure."
},
"results_limit": {
"type": "number",
"default": 12,
"description": "Number of results to return"
}
},
"additionalProperties": false
}

hub_repo_details

Get details for one or more Hugging Face repos (model, dataset, or space). Auto-detects type unless specified. For datasets, use operations: overview, dataset_structure, dataset_preview. Use dataset_structure first to discover configs, splits, sizes, and schema. Use dataset_preview only when config and split are known, unless the dataset has a single config/split.

schema
{
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"required": [
"repo_ids"
],
"properties": {
"limit": {
"type": "integer",
"description": "Row count for dataset_preview. Defaults to 5 and is clamped to 1-100."
},
"split": {
"type": "string",
"description": "Dataset Viewer split. Required for dataset_preview when the dataset has multiple config/split options. Discover via dataset_structure."
},
"config": {
"type": "string",
"description": "Dataset Viewer config. Required for dataset_preview when the dataset has multiple config/split options. Discover via dataset_structure."
},
"offset": {
"type": "integer",
"minimum": 0,
"description": "Row offset for dataset_preview. Defaults to 0."
},
"repo_ids": {
"type": "array",
"items": {
"type": "string",
"minLength": 1
},
"maxItems": 10,
"minItems": 1,
"description": "Repo IDs for (models|dataset/space) - usually in author/name format (e.g. openai/gpt-oss-120b)"
},
"repo_type": {
"enum": [
"model",
"dataset",
"space"
],
"type": "string",
"description": "Specify lookup type; otherwise auto-detects"
},
"operations": {
"type": "array",
"items": {
"enum": [
"overview",
"dataset_structure",
"dataset_preview"
],
"type": "string"
},
"description": "Details to return. Defaults to [\"overview\"]. For datasets, prefer [\"overview\", \"dataset_structure\"] first; then call [\"dataset_preview\"] with config and split."
}
},
"additionalProperties": false
}

hf_doc_search

Search and Discover Hugging Face Product and Library documentation. Send an empty query to discover structure and navigation instructions. Knowledge up-to-date as at 6 May 2026. Combine with the Product filter to focus results.

schema
{
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"required": [
"query"
],
"properties": {
"query": {
"type": "string",
"maxLength": 200,
"description": "Start with an empty query for structure, endpoint discovery and navigation tips. Use semantic queries for targetted searches."
},
"product": {
"type": "string",
"description": "Filter by Product. Supply when known for focused results"
}
},
"additionalProperties": false
}

hf_doc_fetch

Fetch a document from the Hugging Face or Gradio documentation library. For large documents, use offset to get subsequent chunks.

schema
{
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"required": [
"doc_url"
],
"properties": {
"offset": {
"type": "number",
"minimum": 0,
"description": "Token offset for large documents (use the offset from truncation message)"
},
"doc_url": {
"type": "string",
"maxLength": 200,
"description": "Documentation URL (Hugging Face or Gradio)"
}
},
"additionalProperties": false
}

dynamic_space

Perform Tasks with Hugging Face Spaces. Use "discover" to view available Tasks. Examples are Image Generation/Editing, Background Removal, Text to Speech, OCR and many more. Call with no arguments for full usage instructions.

schema
{
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"properties": {
"operation": {
"enum": [
"discover",
"view_parameters",
"invoke"
],
"type": "string",
"description": "Operation to perform."
},
"parameters": {
"type": "string",
"description": "JSON object string of parameters. Only used for \"invoke\" operation."
},
"space_name": {
"type": "string",
"description": "Space ID (format: \"username/space-name\"). Required for \"view_parameters\" and \"invoke\" operations."
}
},
"additionalProperties": false
}

hf_hub_query

Read-only Hugging Face Hub navigator for discovery, lookup, filtering, ranking, counts, field-constrained extraction, and relationship questions across users, orgs, models, datasets, spaces, collections, discussions, daily papers, recent activity, followers/following, likes, and likers. Good for structured raw outputs and compact results. Generated helper calls can explicitly bound limit, scan_limit, max_pages, and ranking_window for brevity or broader coverage, and the tool can also be asked about its supported helpers, canonical fields, defaults, and coverage behavior.

schema
{
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"required": [
"message"
],
"properties": {
"message": {
"type": "string"
}
},
"additionalProperties": false
}

gr1_z_image_turbo_generate

Generate an image using the Z-Image model based on the provided prompt and settings. This function is triggered when the user clicks the "Generate" button. It processes the input prompt (optionally enhancing it), configures generation parameters, and produces an image using the Z-Image diffusion transformer pipeline. Returns: tuple: (gallery_images, seed_str, seed_int), - seed_str: String representation of the seed used for generation, - seed_int: Integer representation of the seed used for generation (from mcp-tools/Z-Image-Turbo)

schema
{
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"properties": {
"seed": {
"type": "integer",
"default": 42,
"description": "Seed for reproducible generation"
},
"shift": {
"type": "number",
"default": 3,
"description": "Time shift parameter for the flow matching scheduler"
},
"steps": {
"type": "number",
"default": 8,
"description": "Number of inference steps for the diffusion process"
},
"prompt": {
"type": "string",
"description": "Text prompt describing the desired image content"
},
"resolution": {
"enum": [
"1024x1024 ( 1:1 )",
"1152x896 ( 9:7 )",
"896x1152 ( 7:9 )",
"1152x864 ( 4:3 )",
"864x1152 ( 3:4 )",
"1248x832 ( 3:2 )",
"832x1248 ( 2:3 )",
"1280x720 ( 16:9 )",
"720x1280 ( 9:16 )",
"1344x576 ( 21:9 )",
"576x1344 ( 9:21 )",
"1280x1280 ( 1:1 )",
"1440x1120 ( 9:7 )",
"1120x1440 ( 7:9 )",
"1472x1104 ( 4:3 )",
"1104x1472 ( 3:4 )",
"1536x1024 ( 3:2 )",
"1024x1536 ( 2:3 )",
"1536x864 ( 16:9 )",
"864x1536 ( 9:16 )",
"1680x720 ( 21:9 )",
"720x1680 ( 9:21 )",
"1536x1536 ( 1:1 )",
"1728x1344 ( 9:7 )",
"1344x1728 ( 7:9 )",
"1728x1296 ( 4:3 )",
"1296x1728 ( 3:4 )",
"1872x1248 ( 3:2 )",
"1248x1872 ( 2:3 )",
"2048x1152 ( 16:9 )",
"1152x2048 ( 9:16 )",
"2016x864 ( 21:9 )",
"864x2016 ( 9:21 )"
],
"type": "string",
"default": "1024x1024 ( 1:1 )",
"description": "Output resolution in format \"WIDTHxHEIGHT ( RATIO )\" (e.g., \"1024x1024 ( 1:1 )\")"
},
"random_seed": {
"type": "boolean",
"default": true,
"description": "Whether to generate a new random seed, if True will ignore the seed input"
}
},
"additionalProperties": false
}