NDWS Wildfire Spread Prediction
by amar-atoumco.huggingface.amar-atoum/ndws-pipeline
Conditional DDPM for next-day wildfire spread prediction
- Remote endpoint
- 3 tools
- MIT
Uptime
Checked · every day
66.78%from 4 days of checks
Up without downtime on 2 of 4 days with data; down 1515 minutes in all, the longest 884 minutes on 31 October.
- No downtime
- Degraded
- Down over 5 minutes
- No data
- Not checked yet
Response time
Median 1257 ms, slowest 5% 1267 ms for the handshake and the tool list, over 30 days.
How far each check got
- Reached the address 100%
- Completed the handshake 33.3%
- Listed its tools 33.3%
3 tools at the last answer.
Every day
| Day | Result | Checks | Median |
|---|---|---|---|
| 3 Nov (today) | No downtime | 1 | 1259 ms |
| 2 Nov | No downtime | 1of 1 | 1048 ms |
| 1 Nov | Down 631 minutes | 1of 1 | 1202 ms |
| 31 Oct | Down 884 minutes | 6 | – |
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://amar-atoum-ndws-pipeline.hf.space/gradio_api/mcp/sse Run in a terminal:
claude mcp add --transport sse ndws-pipeline https://amar-atoum-ndws-pipeline.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": {
"ndws-pipeline": {
"url": "https://amar-atoum-ndws-pipeline.hf.space/gradio_api/mcp/sse"
}
}
} Add to .vscode/mcp.json:
{
"servers": {
"ndws-pipeline": {
"type": "sse",
"url": "https://amar-atoum-ndws-pipeline.hf.space/gradio_api/mcp/sse"
}
}
} Add to ~/.config/zed/settings.json:
{
"context_servers": {
"ndws-pipeline": {
"url": "https://amar-atoum-ndws-pipeline.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": {
"ndws-pipeline": {
"type": "sse",
"url": "https://amar-atoum-ndws-pipeline.hf.space/gradio_api/mcp/sse"
}
}
} Add to ~/.continue/config.yaml:
mcpServers:
- name: "ndws-pipeline"
type: sse
url: "https://amar-atoum-ndws-pipeline.hf.space/gradio_api/mcp/sse" Add to ~/.config/goose/config.yaml:
extensions:
"ndws-pipeline":
type: streamable_http
name: "ndws-pipeline"
enabled: true
uri: "https://amar-atoum-ndws-pipeline.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 ndws-pipeline --url https://amar-atoum-ndws-pipeline.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": {
"ndws-pipeline": {
"url": "https://amar-atoum-ndws-pipeline.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": {
"ndws-pipeline": {
"url": "https://amar-atoum-ndws-pipeline.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": {
"ndws-pipeline": {
"url": "https://amar-atoum-ndws-pipeline.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 NDWS Wildfire Spread Prediction (`co.huggingface.amar-atoum/ndws-pipeline`)
Its page: https://plug.directory/servers/co.huggingface.amar-atoum/ndws-pipeline
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://amar-atoum-ndws-pipeline.hf.space/gradio_api/mcp/sse
```
## Claude Code
Run in a terminal:
```sh
claude mcp add --transport sse ndws-pipeline https://amar-atoum-ndws-pipeline.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": {
"ndws-pipeline": {
"url": "https://amar-atoum-ndws-pipeline.hf.space/gradio_api/mcp/sse"
}
}
}
```
## VS Code
Merge into .vscode/mcp.json:
```json
{
"servers": {
"ndws-pipeline": {
"type": "sse",
"url": "https://amar-atoum-ndws-pipeline.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": {
"ndws-pipeline": {
"type": "sse",
"url": "https://amar-atoum-ndws-pipeline.hf.space/gradio_api/mcp/sse"
}
}
}
```
## Continue
Merge into ~/.continue/config.yaml:
```yaml
mcpServers:
- name: "ndws-pipeline"
type: sse
url: "https://amar-atoum-ndws-pipeline.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": {
"ndws-pipeline": {
"url": "https://amar-atoum-ndws-pipeline.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 3
NDWS_Pipeline_predict_from_libraryPredict next-day wildfire spread with a conditional DDPM ensemble (confidence map, uncertainty map and binary mask) on a bundled NDWS test sample, either shipped with the Space or stored in the weights repository. Returns: Tuple of (input_channels_panel_image, prediction_panel_image with previous fire, ground truth, confidence, uncertainty and binary maps, metrics_markdown_string including IoU, precision, recall and F1 when ground truth is present).NDWS_Pipeline_predict_from_uploadPredict next-day wildfire spread from an uploaded NumPy file with a conditional DDPM ensemble, returning a confidence map (ensemble mean), an uncertainty map (standard deviation across members) and a binary fire mask. 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. Returns: Tuple of (input_channels_panel_image, prediction_panel_image with previous fire, ground truth if present, confidence, uncertainty and binary maps, metrics_markdown_string).NDWS_Pipeline_predict_syntheticPredict next-day wildfire spread on a synthetic homogeneous scenario, where every conditioning channel is a constant 64x64 field. Useful for sensitivity analysis, e.g. sweeping wind speed with everything else held fixed. Returns: Tuple of (input_channels_panel_image, prediction_panel_image with previous fire, confidence, uncertainty and binary maps, metrics_markdown_string).
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