Neural MCP runs on your own machine — the client starts it, so there is no endpoint to ping. 109 installs a week from pypi. Last commit 2 May 2026.
GPU-accelerated MCP server for neural network training, deep learning, and model experimentation
We read the source, 5 d ago · rules 995398eba69f
A value the model can set ends up inside a file or shell call. That is not a flaw by itself — for a terminal server it is the job — but it is where things go wrong when it is not.
return float(eval(func_str, namespace)) # noqa: PGH001
Found in continuous integration, deployment or infrastructure files, or in a neighbouring package of the same monorepo. None of this is installed when you add the server: it describes how the project is built and released. We list it because a leaked key in a build pipeline is still a real problem, but it is not something this server does on your machine.
arr = ensure_array(eval(func_str, namespace).astype(dtype), use_gpu=use_gpu) # noqa: PGH001
Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.
That is not a flaw by itself — but it is where things go wrong when it is not the job. We re-read this code on every release. Watch it and you hear from us the day another one appears.
This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.
claude mcp add neural-mcp -- uvx scicomp-neural-mcp
{
"mcpServers": {
"neural-mcp": {
"command": "uvx",
"args": [
"scicomp-neural-mcp"
]
}
}
}
[mcp_servers.neural-mcp]
command = "uvx"
args = ["scicomp-neural-mcp"]
{
"mcpServers": {
"neural-mcp": {
"command": "uvx",
"args": [
"scicomp-neural-mcp"
]
}
}
}
{
"servers": {
"neural-mcp": {
"type": "stdio",
"command": "uvx",
"args": [
"scicomp-neural-mcp"
]
}
}
}
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Answers built from our own checks of this server.