How do I get a Hugging Face Access Token?

Log in to [**Hugging Face**](https://huggingface.co), go to **Settings > Access Tokens**, click **New token**, give it a name and select scopes (read is sufficient for browsing, write if you need to create repos). Copy the token immediately — it starts with `hf_`.

Can I search models by task type (e.g. text-generation)?

Yes! Use `list_models` with a search query. While the search endpoint doesn't directly filter by pipeline_tag, you can search by task name (e.g. search='text-generation') and then use `get_model` or `get_model_tags` to verify the pipeline_tag of specific models.

Can I see what files are in a model repository?

Yes! Use `list_model_files` with the model ID (e.g. 'google-bert/bert-base-uncased') to see the complete file tree including model weights (.safetensors, .bin), config files, tokenizer files and README. Optionally set a path to browse a specific subdirectory like 'onnx' or 'pytorch'.

Can I create discussions on model pages?

Yes! Use `create_discussion` with the repo type ('model', 'dataset' or 'space'), the repo ID and a title. This creates a new discussion thread on the repository. You can use `list_model_discussions` first to check existing threads before creating a new one.

Hugging Face MCP Server for Cursor 13 tools — connect in under 2 minutes

Name: Hugging Face
Availability: InStock
Author: Vinkius

docs.cursor.com/context/model-context-protocol

Built by Vinkius GDPR 13 Tools IDE

Cursor is an AI-first code editor built on VS Code that integrates LLM-powered coding assistance directly into the development workflow. Its Agent mode enables autonomous multi-step coding tasks, and MCP support lets agents access external data sources and APIs during code generation.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

RecommendedModern Approach — Zero Configuration

Vinkius Desktop App

The modern way to manage MCP Servers — no config files, no terminal commands. Install Hugging Face and 2,500+ MCP Servers from a single visual interface.

Download Free Open SourceNo signup required

Classic Setup·json

{
  "mcpServers": {
    "hugging-face": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Hugging Face MCP Server

Connect your Hugging Face account to any AI agent and explore the world's largest AI model hub through natural conversation.

Cursor's Agent mode turns Hugging Face into an in-editor superpower. Ask Cursor to generate code using live data from Hugging Face and it fetches, processes, and writes. all in a single agentic loop. 13 tools appear alongside file editing and terminal access, creating a unified development environment grounded in real-time information.

What you can do

Model Discovery — Search and browse thousands of models by name, task type, framework and author
Model Inspection — View model metadata including pipeline task, tags, download counts, likes and file structure
Dataset Exploration — Find and inspect datasets with their descriptions, sizes and file trees
Spaces Gallery — Browse ML demo apps (Gradio, Streamlit, Docker) and check their runtime status
Collections — View curated collections of models, datasets and spaces organized by topic
Community Discussions — Read model discussion threads for bug reports, feature requests and usage tips
File Tree Browsing — List repository files (model weights, configs, tokenizers) without downloading

The Hugging Face MCP Server exposes 13 tools through the Vinkius. Connect it to Cursor in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Hugging Face to Cursor via MCP

Follow these steps to integrate the Hugging Face MCP Server with Cursor.

Open MCP Settings

Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"

Add the server config

Paste the JSON configuration above into the mcp.json file that opens

Save the file

Cursor will automatically detect the new MCP server

Start using Hugging Face

Open Agent mode in chat and ask: "Using Hugging Face, help me...". 13 tools available

Why Use Cursor with the Hugging Face MCP Server

Cursor AI Code Editor provides unique advantages when paired with Hugging Face through the Model Context Protocol.

Agent mode turns Cursor into an autonomous coding assistant that can read files, run commands, and call MCP tools without switching context

Cursor's Composer feature can generate entire files using real-time data fetched through MCP. no copy-pasting from external dashboards

MCP tools appear alongside built-in tools like file reading and terminal access, creating a unified agentic environment

VS Code extension compatibility means your existing workflow, keybindings, and extensions all work alongside MCP tools

Hugging Face + Cursor Use Cases

Practical scenarios where Cursor combined with the Hugging Face MCP Server delivers measurable value.

Code generation with live data: ask Cursor to generate a security report module using live DNS and subdomain data fetched through MCP

Automated documentation: have Cursor query your API's tool schemas and generate TypeScript interfaces or OpenAPI specs automatically

Infrastructure-as-code: Cursor can fetch domain configurations and generate corresponding Terraform or CloudFormation templates

Test scaffolding: ask Cursor to pull real API responses via MCP and generate unit test fixtures from actual data

Hugging Face MCP Tools for Cursor (13)

These 13 tools become available when you connect Hugging Face to Cursor via MCP:

create_discussion

Requires the repo type (model, dataset or space), the repo ID in "author/name" format and the discussion title. Returns the created discussion with its ID, title and URL. Create a new discussion on a Hugging Face repo

get_collection

Provide the collection slug. Get details for a specific Hugging Face collection

get_model

Provide the model ID in "author/name" format (e.g. "google-bert/bert-base-uncased"). Get details for a specific Hugging Face model

get_model_tags

Tags include framework (pytorch, tensorflow), license, dataset, language and task-specific labels. The pipeline_tag indicates the model's primary task (e.g. "text-generation", "image-classification", "translation"). Get tags and pipeline info for a Hugging Face model

get_space

Provide the space ID in "author/name" format. Get details for a specific Hugging Face Space

get_user

Returns user name, avatar, organizations, auth type, plan and access tokens metadata. Use this to verify your token is working correctly. Get the authenticated Hugging Face user

list_collections

Optionally filter by author and limit. Returns collection slug, title, description, author, item count and likes count. List collections on Hugging Face Hub

list_dataset_files

Returns filenames (e.g. "train.parquet", "test.parquet", "data/", "README.md"). Optionally set a subdirectory path. Useful for understanding dataset structure before downloading. List files in a Hugging Face dataset repository

list_datasets

Optionally filter by search term, author and limit. Returns dataset ID, author, description, download count, likes count and creation date. List datasets on Hugging Face Hub

list_model_discussions

Returns discussion title, author, creation date, number of comments and whether it is resolved. Use this to review community feedback, bug reports and feature requests for a model. List discussions for a Hugging Face model

list_model_files

Returns filenames, file sizes and paths (e.g. "model.safetensors", "tokenizer.json", "config.json", "README.md"). Optionally set a subdirectory path to list files within a specific folder. Useful for inspecting model artifacts and understanding the repository structure. List files in a Hugging Face model repository

list_models

Optionally filter by search term (free-text across model cards), author (organization or username) and limit the number of results. Returns model ID, author, pipeline task tag, download count, likes count and creation date. List models on Hugging Face Hub

list_spaces

Optionally filter by search term, author and limit. Returns space ID, title, author, SDK (Gradio, Streamlit, Docker), likes count and creation date. List Spaces on Hugging Face Hub

Example Prompts for Hugging Face in Cursor

Ready-to-use prompts you can give your Cursor agent to start working with Hugging Face immediately.

"Find popular text generation models with over 1000 likes."

"Show me what files are in the bert-base-uncased model."

"What discussions are happening on the Llama-3 model page?"

Troubleshooting Hugging Face MCP Server with Cursor

Common issues when connecting Hugging Face to Cursor through the Vinkius, and how to resolve them.

Tools not appearing in Cursor

Ensure you are in Agent mode (not Ask mode). MCP tools only work in Agent mode.

Server shows as disconnected

Check Settings → Features → MCP and verify the server status. Try clicking the refresh button.

Hugging Face + Cursor FAQ

Common questions about integrating Hugging Face MCP Server with Cursor.

What is Agent mode and why does it matter for MCP?

Agent mode is Cursor's autonomous execution mode where the AI can perform multi-step tasks: reading files, editing code, running terminal commands, and calling MCP tools. Without Agent mode, Cursor operates in a simpler ask-and-answer mode that doesn't support tool calling. Always ensure you're in Agent mode when working with MCP servers.

Where does Cursor store MCP configuration?

Cursor looks for MCP server configurations in a mcp.json file. You can configure servers at the project level (.cursor/mcp.json in your project root) or globally (~/.cursor/mcp.json). Project-level configs take precedence.

Can Cursor use MCP tools in inline edits?

No. MCP tools are only available in Agent mode through the chat panel. Inline completions and Tab suggestions do not trigger MCP tool calls. This is by design. tool calls require user visibility and approval.

How do I verify MCP tools are loaded?

Open Settings → Features → MCP and look for your server name. A green indicator means the server is connected. You can also check Agent mode's available tools by clicking the tools dropdown in the chat panel.