NeuroSAM3
by mmrechco.huggingface.mmrech/neurosam3
Agentic neuroimaging — SAM 3, MedSAM, BiomedCLIP, LLM agent
- Remote endpoint
- 11 tools
- APACHE-2.0
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 1080 ms, slowest 5% 1238 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%
11 tools at the last answer.
Every day
| Day | Result | Checks | Median |
|---|---|---|---|
| 3 Nov (today) | No verdict yet | 0 | – |
| 2 Nov | No downtime | 1of 1 | 1097 ms |
| 1 Nov | No downtime | 1of 1 | 1231 ms |
| 31 Oct | No downtime | 2 | 1072 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://mmrech-neurosam3.hf.space/gradio_api/mcp/sseRun in a terminal:
claude mcp add --transport sse neurosam3 https://mmrech-neurosam3.hf.space/gradio_api/mcp/sseAdd 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": {
"neurosam3": {
"url": "https://mmrech-neurosam3.hf.space/gradio_api/mcp/sse"
}
}
}Add to .vscode/mcp.json:
{
"servers": {
"neurosam3": {
"type": "sse",
"url": "https://mmrech-neurosam3.hf.space/gradio_api/mcp/sse"
}
}
}Add to ~/.config/zed/settings.json:
{
"context_servers": {
"neurosam3": {
"url": "https://mmrech-neurosam3.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": {
"neurosam3": {
"type": "sse",
"url": "https://mmrech-neurosam3.hf.space/gradio_api/mcp/sse"
}
}
}Add to ~/.continue/config.yaml:
mcpServers:
- name: "neurosam3"
type: sse
url: "https://mmrech-neurosam3.hf.space/gradio_api/mcp/sse"Add to ~/.config/goose/config.yaml:
extensions:
"neurosam3":
type: streamable_http
name: "neurosam3"
enabled: true
uri: "https://mmrech-neurosam3.hf.space/gradio_api/mcp/sse"
headers: {}
env_keys: []
envs: {}
timeout: 300This 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 neurosam3 --url https://mmrech-neurosam3.hf.space/gradio_api/mcp/sseThis 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": {
"neurosam3": {
"url": "https://mmrech-neurosam3.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": {
"neurosam3": {
"url": "https://mmrech-neurosam3.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": {
"neurosam3": {
"url": "https://mmrech-neurosam3.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 NeuroSAM3 (`co.huggingface.mmrech/neurosam3`)
Its page: https://plug.directory/servers/co.huggingface.mmrech/neurosam3
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://mmrech-neurosam3.hf.space/gradio_api/mcp/sse
```
## Claude Code
Run in a terminal:
```sh
claude mcp add --transport sse neurosam3 https://mmrech-neurosam3.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": {
"neurosam3": {
"url": "https://mmrech-neurosam3.hf.space/gradio_api/mcp/sse"
}
}
}
```
## VS Code
Merge into .vscode/mcp.json:
```json
{
"servers": {
"neurosam3": {
"type": "sse",
"url": "https://mmrech-neurosam3.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": {
"neurosam3": {
"type": "sse",
"url": "https://mmrech-neurosam3.hf.space/gradio_api/mcp/sse"
}
}
}
```
## Continue
Merge into ~/.continue/config.yaml:
```yaml
mcpServers:
- name: "neurosam3"
type: sse
url: "https://mmrech-neurosam3.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": {
"neurosam3": {
"url": "https://mmrech-neurosam3.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 11
NeuroSAM3_agent_chatAgent Chat: send a natural-language request about the uploaded image. The agent (LLM via HF Inference Providers) plans tool calls — BiomedCLIP classification, SAM 3 / MedSAM segmentation, ROI measurement, report — and returns a synthesized answer plus overlay images. 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 toolNeuroSAM3_automatic_masksAutomatic mask generation: a grid of point prompts through the SAM 3 tracker, NMS by IoU. 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 toolNeuroSAM3_clinical_pipelineClinical Pipeline: classify -> segment -> measure -> report in one click. 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 toolNeuroSAM3_compare_ground_truthGround truth: compare SAM 3 (or MedSAM box from GT bbox) with an expert mask -> Dice, IoU, HD95. 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 toolNeuroSAM3_compare_modelsCompare: SAM 3 text vs MedSAM (box from SAM 3) vs SAM 3 tracker (same box); pairwise Dice. 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 toolNeuroSAM3_edge_regionsClassical Canny-based region proposal (no GPU) for quick boundary exploration. 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 toolNeuroSAM3_research_pipelineResearch: batch segmentation with per-subject statistics and a ZIP export bundle. 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 toolNeuroSAM3_segment_interactivePoint & Box: SAM 3 tracker (points/box) or MedSAM (box) interactive segmentation. points_text: 'x,y,label; x,y,label' in pixel coordinates (label 1 = foreground, 0 = background). 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 toolNeuroSAM3_segment_textSegment: SAM 3 text-prompted segmentation with instance table, ROI metrics and exports. 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 toolNeuroSAM3_series_segmentSeries: segment every ordered slice of the selected series with one prompt; estimate volume. 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 toolNeuroSAM3_system_diagnosticsRun a GPU probe (torch/CUDA info, model devices, raw SAM 3 scores on a bundled FLAIR slice) and return the recent application log.
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