ImageGen

by rioshiinaco.huggingface.rioshiina/imagegen

Multi-task image generator with dynamic, chainable workflows

  • Remote endpoint
  • 8 tools

Uptime

Checked  · every day

100%from 4 days of checks

Up without downtime on 3 of 3 days with data.

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

Response time

Median 986 ms, slowest 5% 1000 ms for the handshake and the tool list, over 30 days.

1000 ms500 ms0

How far each check got

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

8 tools at the last answer.

Every day
DayResultChecksMedian
3 Nov (today)No verdict yet0–
2 NovNo downtime1of 1996 ms
1 NovNo downtime1of 1979 ms
31 OctNo downtime2982 ms

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": {
    "imagegen": {
      "url": "https://rioshiina-imagegen.hf.space/gradio_api/mcp/sse"
    }
  }
}
For agents: the install prompt

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

# Install the MCP server ImageGen (`co.huggingface.rioshiina/imagegen`)

Its page: https://plug.directory/servers/co.huggingface.rioshiina/imagegen

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://rioshiina-imagegen.hf.space/gradio_api/mcp/sse
```

## Claude Code

Run in a terminal:

```sh
claude mcp add --transport sse imagegen https://rioshiina-imagegen.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": {
    "imagegen": {
      "url": "https://rioshiina-imagegen.hf.space/gradio_api/mcp/sse"
    }
  }
}
```

## VS Code

Merge into .vscode/mcp.json:

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

## Continue

Merge into ~/.continue/config.yaml:

```yaml
mcpServers:
  - name: "imagegen"
    type: sse
    url: "https://rioshiina-imagegen.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": {
    "imagegen": {
      "url": "https://rioshiina-imagegen.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

  • ImageGen_get_feature_list Get supported advanced features (LoRA, ControlNet, IPAdapter, etc.). Each feature includes ready-to-run example_chain_item and example_json_params. If feature_name is empty, returns summary of ALL features. Pass specific feature_name to retrieve complete parameters_schema.
  • ImageGen_get_model_architecture_list [Recommended Discovery Flow Step 2] Get a list of all supported model architectures (e.g., SD1.5, SDXL, FLUX, etc.) along with their default resolutions and available aspect ratios (with corresponding width & height). It is recommended to call this tool before get_model_list to obtain valid model_architecture parameters for precise model filtering.
  • ImageGen_get_model_features Query metadata for the specified model, including supported task types, extended features, default parameters, and paste-and-run example_json_params.
  • ImageGen_get_model_list [Recommended Discovery Flow Step 3] Query the list of available image generation models. After obtaining models, choose one of two paths: 1. [Path 1 (Recommended - Minimal Mode)] Call run directly with only required parameters. Do NOT guess steps/cfg/sampler/scheduler from experience; the server will automatically apply the model's optimal default hyperparameters. 2. [Path 2 (Explicit Alignment Mode)] First call get_model_features to query the model's officially recommended hyperparameters, then pass them to run.
  • ImageGen_get_sampler_scheduler_list Query all supported Sampler algorithms and Noise Schedulers available for image generation tasks.
  • ImageGen_get_task_list [Recommended Discovery Flow Step 1] Get a list of all supported image generation task types (txt2img, img2img, inpaint, outpaint, hires_fix) along with their required/optional parameters and paste-and-run example_json_params. Recommended flow: get_task_list -> get_model_architecture_list -> get_model_list -> run.
  • ImageGen_get_task_status Query the progress, status, and final generated results of an async image generation task.
  • ImageGen_run [Recommended Discovery Flow Step 4] Unified image generation task execution interface. Accepts a JSON string or dict of parameters. OPTIONAL CONTROL PARAMETERS: - seed (int): Random seed (-1 for random, >=0 for deterministic reproducibility). Default: -1. - batch_size (int): Number of images generated per batch (1 to 16). Default: 1. - zero_gpu_duration (int): GPU quota allocation in seconds on HuggingFace ZeroGPU spaces (default: 60). - negative_prompt (str): Text prompt specifying elements to avoid. IMPORTANT FORMAT RULES FOR 'chain': - For LoRA/Civitai: 'lora_value' refers to the Civitai Version ID (modelVersionId), not the main Model ID. Paste-and-Run Example (Basic): {"task_type": "txt2img", "model": "stabilityai/SDXL-Base-1.0", "prompt": "A majestic lion jumping from a big stone at night", "width": 1024, "height": 1024} Paste-and-Run Example (With chain): {"task_type": "txt2img", "model": "stabilityai/SDXL-Base-1.0", "prompt": "A majestic lion jumping from a big stone at night",

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