Z Image Turbo

by nsfwalexco.huggingface.nsfwalex/imagestudio

How the score works

Install in Augment Code Other clients

Remote endpoint
8 tools

Uptime

Checked 6 Nov, 18:39 UTC · every day

0%from 8 days of checks

Up without downtime on 0 of 7 days with data; down 9537 minutes in all, the longest 1440 minutes on 1 November.

No downtime
Degraded
Down over 5 minutes
No data
Not checked yet

How far each check got

Reached the address 100%
Completed the handshake 0.0%
Listed its tools 0.0%

Every day

Day	Result	Checks	Median
7 Nov (today)	No verdict yet	0	–
6 Nov	Down 1440 minutes	1of 1	–
5 Nov	Down 1440 minutes	1of 1	–
4 Nov	Down 1440 minutes	1of 1	–
3 Nov	Down 1440 minutes	1of 1	–
2 Nov	Down 1440 minutes	1of 1	–
1 Nov	Down 1440 minutes	1of 1	–
31 Oct	Down 897 minutes	9	–

A failure counts as down time only when a second check five minutes later fails too. How we check

Connect to the publisher's own endpoint

Add to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "imagestudio": {
      "url": "https://nsfwalex-imagestudio.hf.space/gradio_api/mcp/sse"
    }
  }
}

Step by step for Cursor

Add to .vscode/mcp.json:

{
  "servers": {
    "imagestudio": {
      "type": "sse",
      "url": "https://nsfwalex-imagestudio.hf.space/gradio_api/mcp/sse"
    }
  }
}

Step by step for VS Code

Add to ~/.config/zed/settings.json:

{
  "context_servers": {
    "imagestudio": {
      "url": "https://nsfwalex-imagestudio.hf.space/gradio_api/mcp/sse"
    }
  }
}

This server's endpoint speaks only SSE, which this client's documentation does not list among its transports; use another client for it.

Step by step for Zed

Add to Augment Settings Panel – MCP section – Import from JSON (VS Code extension):

{
  "mcpServers": {
    "imagestudio": {
      "type": "sse",
      "url": "https://nsfwalex-imagestudio.hf.space/gradio_api/mcp/sse"
    }
  }
}

Step by step for Augment Code

Add to ~/.config/goose/config.yaml:

extensions:
  "imagestudio":
    type: streamable_http
    name: "imagestudio"
    enabled: true
    uri: "https://nsfwalex-imagestudio.hf.space/gradio_api/mcp/sse"
    headers: {}
    env_keys: []
    envs: {}
    timeout: 300

This server's endpoint speaks only SSE, which this client's documentation does not list among its transports; use another client for it.

Step by step for Goose

Run in a terminal:

codex mcp add imagestudio --url https://nsfwalex-imagestudio.hf.space/gradio_api/mcp/sse

This server's endpoint speaks only SSE, which this client's documentation does not list among its transports; use another client for it.

Step by step for Codex

Add to ~/.llm/config.json:

{
  "mcpServers": {
    "imagestudio": {
      "url": "https://nsfwalex-imagestudio.hf.space/gradio_api/mcp/sse"
    }
  }
}

This server's endpoint speaks only SSE, which this client's documentation does not list among its transports; use another client for it.

Step by step for mcp-client-cli

Add to ~/.config/agenvoy/mcp.json:

{
  "servers": {
    "imagestudio": {
      "url": "https://nsfwalex-imagestudio.hf.space/gradio_api/mcp/sse"
    }
  }
}

This server's endpoint speaks only SSE, which this client's documentation does not list among its transports; use another client for it.

Step by step for Agenvoy

Add to ~/.config/amp/settings.json (user) or .amp/settings.json (workspace):

{
  "amp.mcpServers": {
    "imagestudio": {
      "url": "https://nsfwalex-imagestudio.hf.space/gradio_api/mcp/sse"
    }
  }
}

Step by step for Amp

For agents: the install prompt

Every step above as one Markdown text, for an assistant installing it for you.

# Install the MCP server Z Image Turbo (`co.huggingface.nsfwalex/imagestudio`)

Its page: https://plug.directory/servers/co.huggingface.nsfwalex/imagestudio

It runs on the publisher's servers; the client connects to its URL.

Use the section for the person's client.

## Claude Desktop

Paste into Settings › Connectors › Add custom connector:

```text
https://nsfwalex-imagestudio.hf.space/gradio_api/mcp/sse
```

## Claude Code

Run in a terminal:

```sh
claude mcp add --transport sse imagestudio https://nsfwalex-imagestudio.hf.space/gradio_api/mcp/sse
```

## Cursor, Devin Desktop, LM Studio, Gemini CLI, oterm, ECA

Merge into the place for the person's client:

- Cursor: ~/.cursor/mcp.json
- Devin Desktop: ~/.config/devin/mcp_config.json
- LM Studio: mcp.json (Program › Install › Edit mcp.json)
- Gemini CLI: ~/.gemini/settings.json
- oterm: config.json in oterm's data folder (~/Library/Application Support/oterm on macOS, ~/.local/share/oterm on Linux, %APPDATA%\oterm on Windows)
- ECA: ~/.config/eca/config.json (global) or .eca/config.json in the project

```json
{
  "mcpServers": {
    "imagestudio": {
      "url": "https://nsfwalex-imagestudio.hf.space/gradio_api/mcp/sse"
    }
  }
}
```

## VS Code

Merge into .vscode/mcp.json:

```json
{
  "servers": {
    "imagestudio": {
      "type": "sse",
      "url": "https://nsfwalex-imagestudio.hf.space/gradio_api/mcp/sse"
    }
  }
}
```

## Zed

This server's endpoint speaks only SSE, which this client's documentation does not list among its transports; use another client for it.

## Cline, AnythingLLM, Augment Code

Merge into the place for the person's client:

- Cline: cline_mcp_settings.json (MCP Servers › Configure › Configure MCP Servers)
- AnythingLLM: anythingllm_mcp_servers.json in the AnythingLLM storage plugins directory
- Augment Code: Augment Settings Panel – MCP section – Import from JSON (VS Code extension)

```json
{
  "mcpServers": {
    "imagestudio": {
      "type": "sse",
      "url": "https://nsfwalex-imagestudio.hf.space/gradio_api/mcp/sse"
    }
  }
}
```

## Continue

Merge into ~/.continue/config.yaml:

```yaml
mcpServers:
  - name: "imagestudio"
    type: sse
    url: "https://nsfwalex-imagestudio.hf.space/gradio_api/mcp/sse"
```

## Goose

This server's endpoint speaks only SSE, which this client's documentation does not list among its transports; use another client for it.

## Codex

This server's endpoint speaks only SSE, which this client's documentation does not list among its transports; use another client for it.

## mcp-client-cli, TUUI, BoltAI, Bob Shell, Kiro, Kiro CLI

This server's endpoint speaks only SSE, which this client's documentation does not list among its transports; use another client for it.

## Agenvoy

This server's endpoint speaks only SSE, which this client's documentation does not list among its transports; use another client for it.

## Amp

Merge into ~/.config/amp/settings.json (user) or .amp/settings.json (workspace):

```json
{
  "amp.mcpServers": {
    "imagestudio": {
      "url": "https://nsfwalex-imagestudio.hf.space/gradio_api/mcp/sse"
    }
  }
}
```

Then restart the client, or reload its MCP servers, and ask it to list the server's tools to confirm it started.

Tools 8

ImageStudio_apply_model_defaults Update sliders and the negative-prompt controls when the model changes. Sampler defaults + capabilities come from the model's registry entry, so this stays correct for any model the registry knows about.
ImageStudio_assistant_chat Gradio-facing wrapper around ``vlm_chat``. Yields ``(answer, progress)`` so the UI streams the text live and a downstream consumer reading the progress index sees this node advance over SSE. The final ``complete`` frame carries the clean answer at index 0. ``system_prompt`` (optional) steers the assistant. If a user passes a file as an input, use the upload_file_to_gradio tool, if present, to upload the file to the gradio app and create a Gradio File Input. Then use the returned path as the input to the tool
ImageStudio_assistant_chat_1 Gradio-facing wrapper around ``vlm_chat``. Yields ``(answer, progress)`` so the UI streams the text live and a downstream consumer reading the progress index sees this node advance over SSE. The final ``complete`` frame carries the clean answer at index 0. ``system_prompt`` (optional) steers the assistant. If a user passes a file as an input, use the upload_file_to_gradio tool, if present, to upload the file to the gradio app and create a Gradio File Input. Then use the returned path as the input to the tool
ImageStudio_generate_and_upload Generate, then upload the result to R2 outside the GPU window. Generator yielding ``(image, seed, r2_status, progress)``. Streams per-step sampling progress (image still None) and finishes with the real image, seed and R2 status once the upload completes. The image is always the original HF-generated asset; ``r2_status`` reports the uploaded filekey, bucket and a presigned ``r2_url`` on success (or the error on failure) plus the VLM ``moderation`` result. The asset is encoded as **WebP** before upload (and the returned file is WebP too) so downstream consumers only ever see WebP. The caller's unique id (``uid`` cookie) is recorded in the object's metadata.
ImageStudio_generate_and_upload_1 Generate, then upload the result to R2 outside the GPU window. Generator yielding ``(image, seed, r2_status, progress)``. Streams per-step sampling progress (image still None) and finishes with the real image, seed and R2 status once the upload completes. The image is always the original HF-generated asset; ``r2_status`` reports the uploaded filekey, bucket and a presigned ``r2_url`` on success (or the error on failure) plus the VLM ``moderation`` result. The asset is encoded as **WebP** before upload (and the returned file is WebP too) so downstream consumers only ever see WebP. The caller's unique id (``uid`` cookie) is recorded in the object's metadata.
ImageStudio_image_to_video_assets User-uploaded image -> motion prompt + image-context (moderation) check. Generator yielding ``(video_prompt, status, progress)`` per frame so the motion prompt streams and a downstream consumer reading the progress index sees live progress over SSE. ``status`` carries the moderation check once available; the final ``complete`` frame holds the clean prompt at index 0. Bound with ``api_name="image_to_video_assets"`` (hidden trigger, no UI). If a user passes a file as an input, use the upload_file_to_gradio tool, if present, to upload the file to the gradio app and create a Gradio File Input. Then use the returned path as the input to the tool
ImageStudio_moderate_image Standalone moderation endpoint (no UI) for evaluating/tuning the guard. Runs the image-context safety check on a user-supplied image and returns the parsed moderation dict (same shape as the inline checks). Lets us A/B the actual guard model (Qwen 3.5) against the assistant VLM, and try alternate ``MODERATION_PROMPT`` wordings, against fixed images without redeploying for each variant. Bound with api_name="moderate_image". If a user passes a file as an input, use the upload_file_to_gradio tool, if present, to upload the file to the gradio app and create a Gradio File Input. Then use the returned path as the input to the tool
ImageStudio_prompt_to_video_assets Text -> first-frame image (uploaded to R2) + video generation prompt. Streams progress and returns a dict with ``video_prompt``, ``first_frame_url`` (a presigned GET to the **WebP** first frame, usable directly), ``r2_filekey``/``r2_bucket`` (for callers that resolve their own public URL), ``first_frame_prompt`` (the intermediate image prompt), ``moderation`` (the VLM image-context check on the rendered frame) and ``seed``. Has no UI (registered via ``gr.api``).

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