semvec/pypi-packages huggingface dataset:
sbcli-pre-nw 1.0.3
CLI for managing SimplyBlock cluster


# SBCLI (SimplyBlock CLI)

Simplyblock provides a feature-rich CLI (command line interface) to deploy SimplyBlock Cluster and to manage the SimplyBlock Control plane

## Install

The CLI can be installed using pypi package [sbctl](https://pypi.org/project/sbctl/)

```
pip install --upgrade sbctl
```

# Components

## Simply Block Core
Contains core logic and controllers for the simplyblock cluster

## Simply Block CLI
The list of all the available CLI options can be here [CLI docs](./simplyblock_cli/README.md)

## SimplyBlock Web API

Web app that provides API to manage the cluster. More about this in [README.md](./simplyblock_web/README.md)


### local development

FoundationDB requires a client library (libfdb_c.dylib) for the Python bindings to interact with the database.
Depending on the OS architecture, please install the appropriate version from the official github repo

```
wget https://github.com/apple/foundationdb/releases/download/7.3.3/FoundationDB-7.3.3_arm64.pkg
```
setup the code on a management node and the webApp code can be developed by building the `docker-compose-dev.yml` file.

```
sudo docker compose -f docker-compose-dev.yml up --build -d
```
scanpy-mcp 0.5.0
Natural language interface for scRNA-Seq analysis with Scanpy through MCP.
Requires Python: >=3.10
Keywords: AI, agent, bioinformatics, llm, mcp, model context protocol, scRNA-seq, single cell

# Scanpy-MCP

Natural language interface for scRNA-Seq analysis with Scanpy through MCP.

## 🪩 What can it do?

- IO module like read and write scRNA-Seq data
- Preprocessing module,like filtering, quality control, normalization, scaling, highly-variable genes, PCA, Neighbors,...
- Tool module, like clustering, differential expression etc.
- Plotting module, like violin, heatmap, dotplot

## ❓ Who is this for?

- Anyone who wants to do scRNA-Seq analysis natural language!
- Agent developers who want to call scanpy's functions for their applications

## 🌐 Where to use it?

You can use scanpy-mcp in most AI clients, plugins, or agent frameworks that support the MCP:

- AI clients, like Cherry Studio
- Plugins, like Cline
- Agent frameworks, like Agno 


## 📚 Documentation

scmcphub's complete documentation is available at https://docs.scmcphub.org

## 🎬 Demo

A demo showing scRNA-Seq cell cluster analysis in a AI client Cherry Studio using natural language based on scanpy-mcp

https://github.com/user-attachments/assets/93a8fcd8-aa38-4875-a147-a5eeff22a559

## 🏎️ Quickstart

### Install

Install from PyPI
```
pip install scanpy-mcp
```
you can test it by running
```
scanpy-mcp run
```


#### run scnapy-mcp locally
Refer to the following configuration in your MCP client:

check path
```
$ which scanpy 
/home/test/bin/scanpy-mcp
```

```
"mcpServers": {
  "scanpy-mcp": {
    "command": "//home/test/bin/scanpy-mcp",
    "args": [
      "run"
    ]
  }
}
```

#### run scnapy-mcp remotely
Refer to the following configuration in your MCP client:

run it in your server
```
scanpy-mcp run --transport shttp --port 8000
```

Then configure your MCP client in local AI client, like this:
```

"mcpServers": {
  "scanpy-mcp": {
    "url": "http://localhost:8000/mcp"
  }
}
```

## 🤝 Contributing

If you have any questions, welcome to submit an issue, or contact me(hsh-me@outlook.com). Contributions to the code are also welcome!

## Citing
If you use scanpy-mcp in for your research, please consider citing  following work: 
> Wolf, F., Angerer, P. & Theis, F. SCANPY: large-scale single-cell gene expression data analysis. Genome Biol 19, 15 (2018). https://doi.org/10.1186/s13059-017-1382-0