VisualLearningIdea
by kwabshugco.huggingface.kwabshug/visuallearningidea
Visualisation and speed of input attempt
- 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 1130 ms, slowest 5% 1268 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%
6 tools at the last answer.
Every day
| Day | Result | Checks | Median |
|---|---|---|---|
| 3 Nov (today) | No downtime | 1 | 1130 ms |
| 2 Nov | No downtime | 1of 1 | 1203 ms |
| 1 Nov | No downtime | 1of 1 | 1193 ms |
| 31 Oct | No downtime | 2 | 1120 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://kwabshug-visuallearningidea.hf.space/gradio_api/mcp/sse Run in a terminal:
claude mcp add --transport sse visuallearningidea https://kwabshug-visuallearningidea.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": {
"visuallearningidea": {
"url": "https://kwabshug-visuallearningidea.hf.space/gradio_api/mcp/sse"
}
}
} Add to .vscode/mcp.json:
{
"servers": {
"visuallearningidea": {
"type": "sse",
"url": "https://kwabshug-visuallearningidea.hf.space/gradio_api/mcp/sse"
}
}
} Add to ~/.config/zed/settings.json:
{
"context_servers": {
"visuallearningidea": {
"url": "https://kwabshug-visuallearningidea.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": {
"visuallearningidea": {
"type": "sse",
"url": "https://kwabshug-visuallearningidea.hf.space/gradio_api/mcp/sse"
}
}
} Add to ~/.continue/config.yaml:
mcpServers:
- name: "visuallearningidea"
type: sse
url: "https://kwabshug-visuallearningidea.hf.space/gradio_api/mcp/sse" Add to ~/.config/goose/config.yaml:
extensions:
"visuallearningidea":
type: streamable_http
name: "visuallearningidea"
enabled: true
uri: "https://kwabshug-visuallearningidea.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 visuallearningidea --url https://kwabshug-visuallearningidea.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": {
"visuallearningidea": {
"url": "https://kwabshug-visuallearningidea.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": {
"visuallearningidea": {
"url": "https://kwabshug-visuallearningidea.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": {
"visuallearningidea": {
"url": "https://kwabshug-visuallearningidea.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 VisualLearningIdea (`co.huggingface.kwabshug/visuallearningidea`)
Its page: https://plug.directory/servers/co.huggingface.kwabshug/visuallearningidea
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://kwabshug-visuallearningidea.hf.space/gradio_api/mcp/sse
```
## Claude Code
Run in a terminal:
```sh
claude mcp add --transport sse visuallearningidea https://kwabshug-visuallearningidea.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": {
"visuallearningidea": {
"url": "https://kwabshug-visuallearningidea.hf.space/gradio_api/mcp/sse"
}
}
}
```
## VS Code
Merge into .vscode/mcp.json:
```json
{
"servers": {
"visuallearningidea": {
"type": "sse",
"url": "https://kwabshug-visuallearningidea.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": {
"visuallearningidea": {
"type": "sse",
"url": "https://kwabshug-visuallearningidea.hf.space/gradio_api/mcp/sse"
}
}
}
```
## Continue
Merge into ~/.continue/config.yaml:
```yaml
mcpServers:
- name: "visuallearningidea"
type: sse
url: "https://kwabshug-visuallearningidea.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": {
"visuallearningidea": {
"url": "https://kwabshug-visuallearningidea.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
VisualLearningIdea_check_wordsCheck which words of a sentence exist in the 3D vocabulary, and complete the word being typed. A word is available only when a ready asset (SimReady or Objaverse) exists for it; "maps_to" names the asset it would get. Words with no asset are listed in "missing": rephrase them, or map each one to a primitive shape in primitives_json. Verbs (sat, stood, lay, shone, faced) and prepositions (on, under, beside, near, behind, in front of, above) are relations between meshes; whatever "shone" becomes the light source. Returns: JSON string: {"ok", "words": [{text, kind, available_in, maps_to | primitive}], "missing",, "primitive_shapes", "completions"}.VisualLearningIdea_refine_sceneRefine a ledger: freeze some decisions and change the others, then re-render. Changes are a JSON list of: {"id": "n1", "freeze": true} lock an item (false unlocks) {"id": "n1", "use": 2} swap in alternatives[2]; the old choice takes slot 2, so using 2 again swaps back (other slots don't move) {"id": "n1", "reject": true} reject the tier: simready -> objaverse -> primitive -> generation {"id": "n1", "height_m": 0.4} set the object's height in metres {"id": "n1", "shape": "sphere"} use a primitive (box, sphere, cylinder, cone, plane) {"reroll": true} every unfrozen object takes a random alternative Frozen items cannot be changed. The configuration (placement, sun angle) is always re-chosen from `seed`: change the seed for another valid configuration. Returns: (ledger JSON string, rendered PNG, GLB scene file, mini HTML page).VisualLearningIdea_simplify_itemBuild the simplification ladder for one object: full asset -> fewer faces -> convex hull -> box. Look at where the object stops reading as its word: that rung is the least geometry that still carries the meaning, and the low rungs are the ones that can be made physically (fewer faces = fewer papercraft pieces). Returns: (report JSON string, gallery of rung pictures, GLB file per rung,, mini HTML page with the low rungs side by side).VisualLearningIdea_translate_to_sceneTranslate an English sentence into a 3D scene. Produces the serial ledger (tokens in reading order, the items each word commits, and the unresolved questions), one configuration of that ledger chosen by `seed`, a rendered picture, a GLB model and a mini HTML page. The HTML is a self-contained Three.js scene with inline low-poly geometry: read it, edit it, build on it. Words with no asset must be mapped to a primitive in primitives_json (see check_words). Returns: (ledger JSON string, rendered PNG, GLB scene file, mini HTML page).
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