MCP Server Colab Exec

Name: MCP Server Colab Exec
Author: pdwi2020

by pdwi2020version 0.1.0i★ –iRuns on your computer

Registry nameio.github.pdwi2020/mcp-server-colab-exec

Install

Overview

Description from the maker (original English)

Execute Python code on Google Colab GPU runtimes (T4/L4) from any MCP client

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "colab-exec": {
      "command": "uvx",
      "args": [
        "mcp-server-colab-exec"
      ]
    }
  }
}

Run this in your terminal

claude mcp add colab-exec -- uvx mcp-server-colab-exec

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "colab-exec": {
      "command": "uvx",
      "args": [
        "mcp-server-colab-exec"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "colab-exec": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "mcp-server-colab-exec"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account pdwi2020, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

More stars than 0% of the other 32691 servers in this category
Published to the registry more recently than 2% of the other 32691 servers in this category
Basic checks equal to or better than 100% of the other 32691 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is MCP Server Colab Exec safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.0) reached the registry 9 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Dialyne

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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Runs on your computer★ 440MITUpdated 14 months ago

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Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

mcp-server-colab-exec

MCP server that allocates Google Colab GPU runtimes (T4/L4) and executes Python code on them. Lets any MCP-compatible AI assistant — Claude Code, Claude Desktop, Gemini CLI, Cline, and others — run GPU-accelerated code (CUDA, PyTorch, TensorFlow) without local GPU hardware.

Prerequisites

Python 3.10+
A Google account with access to Google Colab
On first run, a browser window opens for OAuth2 consent. The token is cached at ~/.config/colab-exec/token.json for subsequent runs.

Installation

pip install mcp-server-colab-exec

Or run directly with uvx:

uvx mcp-server-colab-exec

Configuration

Claude Code

Add to your project's .mcp.json or ~/.claude/.mcp.json:

"mcpServers": { "colab-exec": { "command": "mcp-server-colab-exec" } } }

Or via the CLI:

claude mcp add colab-exec mcp-server-colab-exec

Claude Desktop

Add to claude_desktop_config.json:

"mcpServers": { "colab-exec": { "command": "mcp-server-colab-exec" } } }

Gemini CLI

gemini mcp add colab-exec -- mcp-server-colab-exec

Tools

`colab_execute`

Execute inline Python code on a Colab GPU runtime.

Parameter	Type	Default	Description
`code`	string	—	Python code to execute (required)
`accelerator`	string	`"T4"`	GPU type: `"T4"` (free) or `"L4"` (premium)
`timeout`	int	`300`	Max execution time in seconds

Returns JSON with per-cell output, errors, and stderr.

`colab_execute_file`

Execute a local .py file on a Colab GPU runtime.

Parameter	Type	Default	Description
`file_path`	string	—	Path to a local `.py` file (required)
`accelerator`	string	`"T4"`	GPU type: `"T4"` (free) or `"L4"` (premium)
`timeout`	int	`300`	Max execution time in seconds

Security policy: file_path must be a .py file inside the current workspace (cwd).

`colab_execute_notebook`

Execute code and collect all generated artifacts (images, CSVs, models, etc.).

Parameter	Type	Default	Description
`code`	string	—	Python code to execute (required)
`output_dir`	string	—	Local directory for downloaded artifacts (required)
`accelerator`	string	`"T4"`	GPU type: `"T4"` (free) or `"L4"` (premium)
`timeout`	int	`300`	Max execution time in seconds

Artifacts are downloaded as a zip and extracted into output_dir. Zip members are validated before extraction to prevent path traversal and special-file writes.

Examples

Check GPU availability:

colab_execute(code="import torch; print(torch.cuda.is_available()); print(torch.cuda.get_device_name(0))")

Run nvidia-smi:

colab_execute(code="import subprocess; print(subprocess.run(['nvidia-smi'], capture_output=True, text=True).stdout)")

Train a model and download weights:

colab_execute_notebook(

code="import torch; model = torch.nn.Linear(10, 1); torch.save(model.state_dict(), '/tmp/model.pt')", output_dir="./outputs" )

Authentication

On first use, the server opens a browser window for Google OAuth2 consent. The access token and refresh token are cached at ~/.config/colab-exec/token.json. Subsequent runs use the cached token and refresh it automatically.

The OAuth2 client credentials are the same ones used by the official Google Colab VS Code extension (google.colab@0.3.0). They are intentionally public.

Troubleshooting

"GPU quota exceeded" — Colab has usage limits. Wait and retry, or use a different Google account.

"Timed out creating kernel session" — The runtime took too long to start. Retry — Colab sometimes has delays during peak usage.

"Authentication failed" — Delete ~/.config/colab-exec/token.json and re-authenticate.

OAuth browser window doesn't open — Ensure you're running in an environment with a browser. For headless servers, authenticate on a machine with a browser first and copy the token file.

License

MIT

MCP Server Colab Exec

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

Dialyne

README from the maker

mcp-server-colab-exec

Prerequisites

Installation

Configuration

Claude Code

Claude Desktop

Gemini CLI

Tools

colab_execute

colab_execute_file

colab_execute_notebook

Examples

Authentication

Troubleshooting

License

`colab_execute`

`colab_execute_file`

`colab_execute_notebook`