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VisualTorch MCP Server

local only

VisualTorch runs on your own machine — the client starts it, so there is no endpoint to ping. 387 installs a week from pypi. Last commit 24 Aug 2026.

Render PyTorch architecture diagrams and animated GIF reveals from trusted model source.

Installs per day peak 134 · avg 64 · -13% w/w
a month agotoday
387
Installs / week
pypi · visualtorch
332
Stars
2 open issues
24 Aug 2026
Last commit
0 releases in 90 days
MIT
License
Python

What the code does

We read the source, 20 h ago · rules 3dff92dd89df

A tool parameter reaches a dangerous call

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.

A tool parameter reaches a dangerous call visualize_model.source → visualtorch_mcp/worker.py:82
    model = eval(model_expression, namespace)  # noqa: S307 - trusted source expression by design.
Capabilities

What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.

        process = subprocess.Popen(  # noqa: S603 - fixed interpreter and module invocation.
    model = eval(model_expression, namespace)  # noqa: S307 - trusted source expression by design.

Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.

A tool parameter here reaches a dangerous call

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.

Three servers free · no card

Connect this server

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.

run in your terminal
claude mcp add visualtorch -- uvx visualtorch
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "visualtorch": {
      "args": [
        "visualtorch"
      ],
      "command": "uvx"
    }
  }
}
~/.codex/config.toml
[mcp_servers.visualtorch]
command = "uvx"
args = ["visualtorch"]
.cursor/mcp.json
{
  "mcpServers": {
    "visualtorch": {
      "args": [
        "visualtorch"
      ],
      "command": "uvx"
    }
  }
}
.vscode/mcp.json
{
  "mcpServers": {
    "visualtorch": {
      "args": [
        "visualtorch"
      ],
      "command": "uvx"
    }
  }
}

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VisualTorch — questions

Answers built from our own checks of this server.

Why is there no uptime for VisualTorch?
VisualTorch runs on your own machine over stdio — there is no network address to reach, so uptime cannot be measured for it by anyone. What can be measured is adoption: the pypi package visualtorch was installed 387 times last week.
How do I connect VisualTorch?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It runs locally, so the command pulls visualtorch straight from pypi; nothing to host, nothing to sign up for.
How many people use VisualTorch?
The pypi package visualtorch was installed 387 times in the last week. Week over week that is -13%. We show installs rather than GitHub stars on purpose: a star is a bookmark, an install is someone actually running it.
Is VisualTorch open source?
Yes — it is published under the MIT licence, written in Python, 332 stars on GitHub and 2 open issues. The source link is on this page, so you can read exactly what it does with your data before you connect it.