Tafsut Forecast

by tafsut-fmco.huggingface.tafsut-fm/tafsut-forecast-demo

Zero-shot probabilistic time-series forecasting

  • Remote endpoint
  • 4 tools

Uptime

Checked  · every day

100%from 4 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 1158 ms, slowest 5% 1318 ms for the handshake and the tool list, over 30 days.

1500 ms750 ms0

How far each check got

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

4 tools at the last answer.

Every day
DayResultChecksMedian
3 Nov (today)No downtime11318 ms
2 NovNo downtime1of 11141 ms
1 NovNo downtime1of 11222 ms
31 OctNo downtime11214 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 ~/.config/eca/config.json (global) or .eca/config.json in the project:

{
  "mcpServers": {
    "tafsut-forecast-demo": {
      "url": "https://tafsut-fm-tafsut-forecast-demo.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 Tafsut Forecast (`co.huggingface.tafsut-fm/tafsut-forecast-demo`)

Its page: https://plug.directory/servers/co.huggingface.tafsut-fm/tafsut-forecast-demo

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://tafsut-fm-tafsut-forecast-demo.hf.space/gradio_api/mcp/sse
```

## Claude Code

Run in a terminal:

```sh
claude mcp add --transport sse tafsut-forecast-demo https://tafsut-fm-tafsut-forecast-demo.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": {
    "tafsut-forecast-demo": {
      "url": "https://tafsut-fm-tafsut-forecast-demo.hf.space/gradio_api/mcp/sse"
    }
  }
}
```

## VS Code

Merge into .vscode/mcp.json:

```json
{
  "servers": {
    "tafsut-forecast-demo": {
      "type": "sse",
      "url": "https://tafsut-fm-tafsut-forecast-demo.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": {
    "tafsut-forecast-demo": {
      "type": "sse",
      "url": "https://tafsut-fm-tafsut-forecast-demo.hf.space/gradio_api/mcp/sse"
    }
  }
}
```

## Continue

Merge into ~/.continue/config.yaml:

```yaml
mcpServers:
  - name: "tafsut-forecast-demo"
    type: sse
    url: "https://tafsut-fm-tafsut-forecast-demo.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": {
    "tafsut-forecast-demo": {
      "url": "https://tafsut-fm-tafsut-forecast-demo.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 4

  • tafsut_forecast_demo__adaptive_history_slider Adapt the history display range to the currently supplied series. Short series default to showing their full history. Longer series default to the latest 2,048 points while allowing the slider to expand to the complete model context (up to 32,768 points). 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
  • tafsut_forecast_demo__adaptive_history_slider_1 Adapt the history display range to the currently supplied series. Short series default to showing their full history. Longer series default to the latest 2,048 points while allowing the slider to expand to the complete model context (up to 32,768 points). 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
  • tafsut_forecast_demo_run_forecast Generate a probabilistic time-series forecast with Tafsut. Upload a CSV file (single column of numeric values) or paste comma-separated values. The model produces quantile forecasts with uncertainty bands. 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
  • tafsut_forecast_demo_run_forecast_1 Generate a probabilistic time-series forecast with Tafsut. Upload a CSV file (single column of numeric values) or paste comma-separated values. The model produces quantile forecasts with uncertainty bands. 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

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