ImageGen
by or1290co.huggingface.or1290/lp12
Multi-task image generator with dynamic, chainable workflows
- Remote endpoint
- 8 tools
Uptime
Checked · every day
100%from 5 days of checks
Up without downtime on 4 of 4 days with data.
- No downtime
- Degraded
- Down over 5 minutes
- No data
- Not checked yet
Response time
Median 1059 ms, slowest 5% 1197 ms for the handshake and the tool list, over 30 days.
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
| Day | Result | Checks | Median |
|---|---|---|---|
| 3 Nov (today) | No verdict yet | 0 | – |
| 2 Nov | No downtime | 1of 1 | 1123 ms |
| 1 Nov | No downtime | 1of 1 | 1128 ms |
| 31 Oct | No downtime | 1of 1 | 1129 ms |
| 30 Oct | No downtime | 1 | 982 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
Paste into Settings › Connectors › Add custom connector:
https://or1290-lp12.hf.space/gradio_api/mcp/sse Run in a terminal:
claude mcp add --transport sse lp12 https://or1290-lp12.hf.space/gradio_api/mcp/sse Add to ~/.cursor/mcp.json:
Add to ~/.config/devin/mcp_config.json:
Add to mcp.json (Program › Install › Edit mcp.json):
Add to ~/.gemini/settings.json:
Add to config.json in oterm's data folder (~/Library/Application Support/oterm on macOS, ~/.local/share/oterm on Linux, %APPDATA%\oterm on Windows):
Add to ~/.config/eca/config.json (global) or .eca/config.json in the project:
{
"mcpServers": {
"lp12": {
"url": "https://or1290-lp12.hf.space/gradio_api/mcp/sse"
}
}
} Add to .vscode/mcp.json:
{
"servers": {
"lp12": {
"type": "sse",
"url": "https://or1290-lp12.hf.space/gradio_api/mcp/sse"
}
}
} Add to ~/.config/zed/settings.json:
{
"context_servers": {
"lp12": {
"url": "https://or1290-lp12.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.
Add to cline_mcp_settings.json (MCP Servers › Configure › Configure MCP Servers):
Add to anythingllm_mcp_servers.json in the AnythingLLM storage plugins directory:
Add to Augment Settings Panel – MCP section – Import from JSON (VS Code extension):
{
"mcpServers": {
"lp12": {
"type": "sse",
"url": "https://or1290-lp12.hf.space/gradio_api/mcp/sse"
}
}
} Add to ~/.continue/config.yaml:
mcpServers:
- name: "lp12"
type: sse
url: "https://or1290-lp12.hf.space/gradio_api/mcp/sse" Add to ~/.config/goose/config.yaml:
extensions:
"lp12":
type: streamable_http
name: "lp12"
enabled: true
uri: "https://or1290-lp12.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.
Run in a terminal:
codex mcp add lp12 --url https://or1290-lp12.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.
Add to ~/.llm/config.json:
Add to resources/assets/config/mcp.json in the installed app:
Add to ~/.boltai/mcp.json:
Add to ~/.bob/settings/mcp.json (global) or .bob/mcp.json (project):
Add to ~/.kiro/settings/mcp.json (user) or .kiro/settings/mcp.json (workspace):
Add to ~/.kiro/settings/mcp.json (user) or .kiro/settings/mcp.json (workspace):
{
"mcpServers": {
"lp12": {
"url": "https://or1290-lp12.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.
Add to ~/.config/agenvoy/mcp.json:
{
"servers": {
"lp12": {
"url": "https://or1290-lp12.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.
Add to ~/.config/amp/settings.json (user) or .amp/settings.json (workspace):
{
"amp.mcpServers": {
"lp12": {
"url": "https://or1290-lp12.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.or1290/lp12`)
Its page: https://plug.directory/servers/co.huggingface.or1290/lp12
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://or1290-lp12.hf.space/gradio_api/mcp/sse
```
## Claude Code
Run in a terminal:
```sh
claude mcp add --transport sse lp12 https://or1290-lp12.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": {
"lp12": {
"url": "https://or1290-lp12.hf.space/gradio_api/mcp/sse"
}
}
}
```
## VS Code
Merge into .vscode/mcp.json:
```json
{
"servers": {
"lp12": {
"type": "sse",
"url": "https://or1290-lp12.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": {
"lp12": {
"type": "sse",
"url": "https://or1290-lp12.hf.space/gradio_api/mcp/sse"
}
}
}
```
## Continue
Merge into ~/.continue/config.yaml:
```yaml
mcpServers:
- name: "lp12"
type: sse
url: "https://or1290-lp12.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": {
"lp12": {
"url": "https://or1290-lp12.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
LP12_get_feature_listGet 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.LP12_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.LP12_get_model_featuresQuery metadata for the specified model, including supported task types, extended features, default parameters, and paste-and-run example_json_params.LP12_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.LP12_get_sampler_scheduler_listQuery all supported Sampler algorithms and Noise Schedulers available for image generation tasks.LP12_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.LP12_get_task_statusQuery the progress, status, and final generated results of an async image generation task.LP12_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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