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MCP Hfspace

by evalstate

Connect Claude Desktop to Hugging Face Spaces for image, audio, text, vision, and chat tasks.

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Install MCP Hfspace

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "evalstate-mcp-hfspace": {
      "command": "npx",
      "args": [
        "-y",
        "@llmindset/mcp-hfspace"
      ],
      "env": {
        "MCP_HF_WORK_DIR": "YOUR_VALUE_HERE",
        "HF_TOKEN": "YOUR_VALUE_HERE",
        "CLAUDE_DESKTOP_MODE": "YOUR_VALUE_HERE"
      }
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Values are written into the snippet above so you can paste it as is. They never leave your browser.

We couldn’t confirm it starts correctly

The install command started, but didn't respond the way we expected when we tried to talk to it.

npx -y @llmindset/mcp-hfspace

initialize succeeded but no response to tools/list.

This is an experimental automated check and can have false negatives — missing environment variables, a slow cold install, etc. It doesn’t necessarily mean something’s wrong. Last checked 1mo ago.

Overview

The evalstate/mcp-hfspace MCP server connects Claude Desktop to Hugging Face Spaces through configurable MCP tools. It can discover Spaces, call configured endpoints, and handle image, audio, text, and other file inputs and outputs. Use the evalstate/mcp-hfspace MCP server when you want Claude to access hosted Gradio or Hugging Face workloads without building separate API integrations. Public Spaces need minimal setup, while private Spaces require a Hugging Face token.

Use cases

  • Generate images with Hugging Face Spaces
  • Analyze local images with vision Spaces
  • Transcribe audio through speech-to-text Spaces
  • Create speech or other audio outputs
  • Query chat-oriented Hugging Face models

Key features

  • Search Hugging Face Spaces semantically
  • Call configured Space endpoints over MCP
  • Upload files from a working directory or URL
  • Save generated files locally
  • Support private Spaces with a Hugging Face token
  • Expose available local resources to the client

Tools3

What MCP Hfspace lets your agent do. Expand a tool for its parameters.

Verified live~345 tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked Today

Recent health check succeeded.

20/20 checks healthy over the last 77d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 8d ago via OSV.dev · @llmindset/mcp-hfspace (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars390Stargazers on the source repository.
npm downloads570Package downloads in the last 30 days.
Last commit1y agoMost recent push to the default branch.
Install checkInconclusiveStarted but did not complete the MCP handshake in our test.
Tools exposed3Callable tools this server registers over MCP.
Directory activity7 viewsConfig copies, upvotes, and views on AllMCPs.

How MCP Hfspace works

What evalstate/mcp-hfspace MCP server does

The evalstate/mcp-hfspace MCP server exposes Hugging Face Spaces to an MCP client, with Claude Desktop as the documented client. It is intended for tasks such as image generation, chat, vision analysis, text-to-speech, speech-to-text, image-to-image processing, and other Space-supported operations.

The server can be started with one or more Space names. It finds an appropriate endpoint and creates tools for interacting with those Spaces. A specific endpoint can also be selected by appending its endpoint path to the Space name.

How it works

The server provides a semantic Space search tool, a resource listing tool, and endpoint-specific tools. search-spaces finds possible Hugging Face Spaces from a short task description and returns the matches in a table. available-files reports files in the configured working directory, including names, sizes, modification times, MIME types, and resource URIs.

Configured Spaces receive inputs from the MCP client. Inputs may include local filenames or URLs. Depending on the client mode and file type, generated content is either included in the response or written to the working directory. In Claude Desktop Mode, images are returned in tool responses, while other files are saved locally and their paths are reported.

Setup and configuration

Install Node.js and add the npm package @llmindset/mcp-hfspace to the mcpServers section of Claude Desktop’s configuration. The documented command uses npx -y, followed by the package name and any Space names. Claude Desktop 0.78 or newer is required according to the setup instructions.

Set a working directory with --work-dir=/path or the MCP_HF_WORK_DIR environment variable. This directory is used for uploaded and downloaded files. The default depends on the current working directory and the operating system, so specifying one is recommended for predictable file handling.

Private Spaces require a Hugging Face token supplied through --hf-token or HF_TOKEN. The evalstate/mcp-hfspace MCP server can run multiple instances when separate working directories or tokens are needed. Claude Desktop Mode can be disabled with --desktop-mode=false or CLAUDE_DESKTOP_MODE=false, causing files to be returned as embedded Base64 resources instead.

Tools and capabilities

The listed tools include:

  • available-files for identifying local resources such as recent images or audio files.
  • search-spaces for finding Hugging Face Space endpoints by task description.
  • FLUX_1-schnell-infer for calling the default FLUX.1-schnell inference endpoint.

Configured Spaces can support image, audio, and text uploads and downloads. Actual inputs and outputs depend on the selected Space and endpoint.

Limitations and notes

The repository README states that this project has been superseded by Hugging Face’s official MCP Server and Gradio MCP Endpoints. It also points to hf.co/mcp as a way to access and configure Hugging Face MCP services directly.

Space metadata and input labels may not always be clear, although the server generates prompts and tool descriptions from each Space. The available resources mechanism is intended to help the client identify files in the working directory. Claude Desktop does not support transmitting resources from within context, so specifying a filename is recommended when a file should be uploaded directly to a Space.

Read the full README View source on GitHub

Reviews

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Frequently Asked Questions about MCP Hfspace

Install Node.js, then add the `npx -y @llmindset/mcp-hfspace` command to the `mcpServers` section of Claude Desktop’s configuration.

Yes.

Provide a Hugging Face token with the `--hf-token` argument or the `HF_TOKEN` environment variable.

Use the `--work-dir=/path` argument or set `MCP_HF_WORK_DIR`.

Yes. The documented examples cover image generation, audio generation, speech-to-text, vision, chat, and image-to-image processing through configured Spaces.

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