Colab-MCP (unofficial)

Name: Colab-MCP (unofficial)
Author: amgallego8

de amgallego8versión 0.1.0i★ –iSe ejecuta en tu computadora

Nombre en el registroio.github.amgallego8/colab-mcp

Instalar

Resumen

Descripción del creador (original en inglés)

Unofficial MCP server for Google Colab: runtimes, code, long jobs, files and notebooks.

Los tres pilares de PopNx MCP

Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.

Opinión de usuariosiAún no hay reseñasLas reseñas se abrirán junto con las cuentas en una etapa posterior
Nuestras revisiones básicasi1 de 1 superadasRevisado con información pública; el código aún no se ha escaneado
UsoiMuy nuevo↓ 77/sem · ★ –

Qué puedes hacer con él

Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.

Conexión: Se ejecuta en tu computadora
Transporte: stdio
Categoría: Documentos, hojas de cálculo y oficina

Instalación

Elige la app de IA que usas y copia la configuración.

Antes de instalar

Revisiones básicas: 1 de 1 superadas
Se ejecuta en tu computadora con los permisos de tu usuario (archivos, red, apps).
Debes completar tú: COLAB_MCP_WORKDIR, COLAB_MCP_DRIVE

Necesitas

PyPIuv de Python instalado (para el comando uvx)

¿Qué app usas?

ClaudeClaude CodeCursorVS CodeChatGPT

Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.

Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json

{
  "mcpServers": {
    "colab": {
      "command": "uvx",
      "args": [
        "colab-cli-mcp"
      ],
      "env": {
        "COLAB_MCP_WORKDIR": "your-value",
        "COLAB_MCP_DRIVE": "your-value"
      }
    }
  }
}

Ejecuta esto en tu terminal

claude mcp add colab --env COLAB_MCP_WORKDIR=your-value --env COLAB_MCP_DRIVE=your-value -- uvx colab-cli-mcp

Completa los valores vacíos antes de ejecutarlo.

Abrir en Cursor

O copia la configuración tú

Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json

{
  "mcpServers": {
    "colab": {
      "command": "uvx",
      "args": [
        "colab-cli-mcp"
      ],
      "env": {
        "COLAB_MCP_WORKDIR": "your-value",
        "COLAB_MCP_DRIVE": "your-value"
      }
    }
  }
}

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

Abrir en VS Code

O copia la configuración tú

Pégalo en .vscode/mcp.json de tu proyecto

{
  "servers": {
    "colab": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "colab-cli-mcp"
      ],
      "env": {
        "COLAB_MCP_WORKDIR": "your-value",
        "COLAB_MCP_DRIVE": "your-value"
      }
    }
  }
}

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.

Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.

Valores que debes completar

COLAB_MCP_WORKDIR env
The only local folder the server reads and writes. Defaults to the current directory.
COLAB_MCP_DRIVE env
Set to 1 to enable the optional Google Drive tools (they need a one-time sign-in, see the README).

Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.

Qué puede hacer

Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.

Revisiones básicasi

Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 9 nov 2026

✓ Superada
El creador coincide con el repo
El nombre en el registro se verificó con la cuenta de GitHub amgallego8, dueña del repo
… Aún sin revisar
Sigue en mantenimiento
Todavía no hemos leído este repo en GitHub
… Aún sin revisar
Tiene licencia
Todavía no hemos leído este repo en GitHub
– No aplica
El endpoint responde
Este se ejecuta en tu computadora; no hay endpoint en internet
– No aplica
Inicio de sesión con OAuth
Se ejecuta en tu computadora y usa ajustes locales en su lugar
… Aún sin revisar
Sin instrucciones ocultas en las descripciones de herramientas
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet

Comparado con otros en Documentos, hojas de cálculo y oficinai

Más estrellas que el 0% de los otros 3599 servidores de esta categoría
Publicado en el registro más recientemente que el 57% de los otros 3599 servidores de esta categoría
Revisiones básicas iguales o mejores que el 100% de los otros 3599 servidores de esta categoría

Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.

Preguntas frecuentes

¿Es seguro Colab-MCP (unofficial)?

Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.

¿Qué claves o códigos necesita?

El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.

¿Se ejecuta en mi computadora o en la nube?

Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).

¿Sigue en mantenimiento?

El repo de GitHub cambió por última vez –, y la última versión (0.1.0) llegó al registro hace 24 días.

¿Qué apps pueden usarlo?

Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) en tu computadora.

¿Qué puedo usar en su lugar?

En la misma categoría: Agent-Native Calendar, Excel MCP Server, MCP Server for Excel

Alternativas

Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.

Cómo leer una tarjeta:↓ Descargas por semanai★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi

Agent-Native Calendar

Agent-Native Google Calendar - manage events, sync, and public booking

de BuilderIOMuy usado★ 7,6 milActualizado hace 2 meses

Se ejecuta en la nube

Instalar

Excel MCP Server

Create and edit Excel files with AI: charts, PivotTables, formulas. No Excel needed.

de haris-musaMuy usado↓ 49,6 mil/sem★ 4,3 milActualizado hace 8 días

Se ejecuta en tu computadora

Instalar

MCP Server for Excel

Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.

de sbroenneEn crecimiento↓ 4,3 mil/sem★ 847Actualizado hace 5 días

Se ejecuta en tu computadora

Instalar

README del creador

Abrir el README

Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.

Colab-MCP

An MCP server that lets an AI agent (Claude, or any MCP client) use Google Colab end to end: create and stop GPU/TPU runtimes, run code, work in notebooks cell by cell, launch long background jobs, and move files and folders in and out of the VM.

It is a thin, safe layer over Google's official Colab CLI (google-colab-cli). It does not reimplement Colab and does not depend on a browser tab.

🇪🇸 Resumen en español al final de este archivo.

Quick start

You need uv and the official Colab CLI, signed in once (macOS or Linux):

uv tool install google-colab-cli

colab sessions # sign in ONCE (open the link, paste the code) claude mcp add colab-cli -e COLAB_MCP_WORKDIR="$HOME/colab-work" -- uvx colab-cli-mcp

That registers the server in Claude Code, and uvx downloads it from PyPI the first time. For Claude Desktop, other clients, secrets and the optional Drive tools, see Install.

Status

Tested against a simulated CLI (118 checks, plus 129 for Drive against a simulated Drive API, 28 for the Drive mount and 17 for local cleanup; tests/): a real MCP client talks to the server over stdio and the code that normally runs on the VM is executed for real in a sandbox folder.
Validated live once. On a real Colab session (macOS, Claude as the client): creating a runtime, running code, a long background job with log polling, mounting Drive from the chat (below) and stopping the session, with one real batch workload (10 items, 0 errors). That is a single run, not a benchmark.
Published on PyPI as colab-cli-mcp 0.1.0. The published package was installed in a clean environment (pip, and uvx) and listed its 42 tools over stdio. That check ran on Linux; use of the uvx route with Claude on macOS has not been checked yet.
Not yet validated live: the Google Drive API tools (drive_*), notebook execution cell by cell, folder uploads and downloads, and the behaviours listed under *Known unknowns*. Other MCP clients (Cursor, Codex, Windsurf) and Linux are untested.
Linux and macOS only (the Colab CLI does not support Windows).

Tools (42 + 8 optional Drive tools)

Area	Tools
Runtimes	`colab_new`, `colab_ensure_session`, `colab_sessions`, `colab_status`, `colab_runtime_info`, `colab_restart_kernel`, `colab_url`, `colab_usage`, `colab_stop`, `colab_install`
Run code	`colab_exec` (code or file; kernel state persists between calls), `colab_run` (one-shot: fresh VM → script → release)
Notebooks (local `.ipynb`)	`colab_notebook_create`, `_list`, `_read`, `_add_cell`, `_edit_cell`, `_delete_cell`, `_move_cell`, `_clear_outputs`, `_run_cell`, `_run_all`, `_to_script`, `_delete`
Long jobs	`colab_job_start`, `_status`, `_logs`, `_cancel`, `_list`
Files	`colab_upload`, `colab_download`, `colab_upload_dir`, `colab_download_dir`, `colab_ls`, `colab_rm`, `colab_log`
Drive on the VM	`colab_drive_status`, `colab_drive_mount_start`, `colab_drive_mount_finish`, `colab_drive_project_dir` (see Big projects and Drive)
Local footprint	`colab_local_footprint`, `colab_local_cleanup` (see Where things live)

Typical flows:

Interactive: colab_ensure_session(gpu="T4") → colab_notebook_create → add cells → colab_notebook_run_cell one by one (variables persist) → read outputs → colab_stop.
Batch: colab_upload_dir → colab_job_start("python -u train.py") → poll colab_job_logs → colab_download_dir → colab_stop.

Google Drive projects and notebooks are a separate, opt-in feature (below). Deliberately not included anywhere: sign-in through a tool, colab auth, repl, console, ssh, edit. They are interactive and cannot work through a tool call.

Security model

Local paths are confined to COLAB_MCP_WORKDIR. ../, absolute paths and symlinks that escape are rejected before anything runs.
Secrets never reach the model. COLAB_MCP_ENV_FILE points to a local NAME=value file. The model only passes names (secrets=["OPENROUTER_API_KEY"]); values go to the kernel with --env and are scrubbed from every result. Known limit: while the command runs, the value is visible to other local users in the process list, because the CLI takes it as an argument.
No shell. The CLI is run with an argument list. Session names, GPU types, package specifiers and job ids are validated. Everything user-controlled that is embedded in code for the VM goes through repr().
Folder transfers are guarded. Uploads skip .git, caches, symlinks and likely secrets (.env, *.pem, *.key…); downloads reject archives with paths that escape the target (zip-slip) or exceed a size limit.
No hard deletes on your computer. colab_notebook_delete moves the file to .colab-mcp-trash/. colab_rm only touches the VM and refuses root-like paths.
Output is clipped to COLAB_MCP_MAX_OUTPUT characters, and terminal colour codes (tracebacks) are stripped.
Code you run executes on Google's machines under your account and spends your compute units. Stop sessions you no longer need.

Big projects and Drive on the VM

For big datasets, checkpoints or results that must survive the session, mount Google Drive on the VM. This is separate from the optional "Drive notebooks" feature below and uses the Colab CLI's own sign-in.

Mount it from the chat, no terminal. colab_drive_mount_start runs the official colab drivemount in a pseudo-terminal (the CLI itself never opens a browser; it only prints a link and waits for Enter), opens Google's approval page in your browser. The link is not repeated in the chat (it contains your account e-mail); it is only returned if the browser could not be opened or with show_link=true. You click Allow (the agent never sees credentials or codes) and tell the agent; colab_drive_mount_finish then sends the Enter the CLI was waiting for and colab_drive_status confirms. Only https://*.google.com links are ever opened, a pending mount is killed after 15 minutes, and there is at most one per session. If you prefer, colab drivemount -s SESSION in a terminal still works. Mounting gives code running on that VM access to your whole Drive (Colab cannot scope it); only mount when you need it and stop the session afterwards.
The agent calls colab_drive_project_dir("my-project"), which creates /content/drive/MyDrive/Colab-MCP/my-project and returns the path. Datasets, checkpoints and outputs go there.
Stop the session when done. Files in that Drive folder remain; everything else on the VM is lost.

Guardrail: the file tools (colab_upload*, colab_download*, colab_ls, colab_rm) refuse any Drive path outside `/content/drive/MyDrive/Colab-MCP/` (folder name configurable with COLAB_MCP_DRIVE_PROJECTS), including .., relative and case tricks. colab_drive_status never lists your files.

Residual risk, stated plainly: once Drive is mounted, *any code that runs on the VM* (colab_exec, colab_run, jobs, notebook cells) can read and change all of your Drive; the path guard only covers this server's file tools, and it cannot see symlinks created on the VM. Mount only when you need it, review the code you run, and stop the session afterwards.

Where things live (and how little stays on your computer)

Where	What	Why
The Colab VM disk (about 200 GB free observed on a T4 ⚠️ not guaranteed)	Datasets, training, anything heavy	Fast, free, gone when the session stops
Drive, folder `Colab-MCP/ /`	Notebooks and results that must persist	Survives sessions; the only part of Drive this tool can see
Your computer	Almost nothing: a temporary working copy while you edit a notebook	Auto-cleaned (below)

Local footprint rules (footprint.py):

Transfer zips are removed right after use and swept after 1 hour; saved plots after 2 days (COLAB_MCP_IMAGE_DAYS); locally "deleted" notebooks after 7 days (COLAB_MCP_TRASH_DAYS, 0 = keep); working copies of Drive notebooks after 24 h (COLAB_MCP_DRIVE_COPY_HOURS, 0 = keep) and immediately when you save. The sweep runs when the server starts and on colab_local_cleanup.
Only files inside .colab-mcp/ and .colab-mcp-trash/ are ever removed. Symlinks are not followed. Your own notebooks and data are never touched.
Guards before downloads: at least COLAB_MCP_MIN_FREE_GB (default 5) must stay free on the disk and the working folder may not exceed COLAB_MCP_WORKDIR_MAX_GB (default 20, 0 = no cap). colab_local_footprint shows the numbers. Keep big data on the VM or in Drive and download only results.

Google Drive: projects and notebooks (opt-in)

Off by default. With COLAB_MCP_DRIVE=1 (the installer sets it when you set Drive up) these tools appear, and only these:

Tool	What it does
`drive_sign_in`	Opens a browser window on your computer where you click Allow. No code or token ever passes through the chat
`drive_project_create` / `drive_project_list`	One folder per Colab project inside `Colab-MCP`. Folders can be created, never deleted or renamed
`drive_notebook_create`	Creates a notebook (empty starter, or a local `.ipynb` with outputs stripped), optionally inside a project
`drive_notebook_list`	Lists the notebooks this server created
`drive_notebook_open` / `drive_notebook_save`	Download a notebook to a temporary local copy, edit it with the `colab_notebook_*` tools, write the content back to the same file. Saving removes the local copy
`drive_notebook_delete`	Moves one of them to the Drive trash (never permanent)

Layout in your Drive: Colab-MCP/ / .ipynb. The Google permission (drive.file) only reaches files and folders this app created, so your existing "Colab Notebooks" folder and everything else stay invisible to it.

A skill that keeps the agent to exactly this lives in skills/colab-drive-notebooks/SKILL.md: copy that folder to ~/.claude/skills/ (Claude Code) or add it as a skill in your client.

Who is responsible for what

Nobody shares credentials. Each user signs in themselves, and the token lives only on their own disk. You choose once between two OAuth clients (below); this project never sees your token. The model never sees a sign-in link, code or token.

Quick start (every user)

From PyPI:

uvx --from colab-cli-mcp colab-cli-mcp-drive login     # asks once how you want to sign in, remembers it, signs you in

claude mcp add colab-cli -e COLAB_MCP_WORKDIR="$HOME/colab-work" -e COLAB_MCP_DRIVE=1 -- uvx colab-cli-mcp

From a clone of this repository, bash install.sh asks "Set up Drive now?", runs the one-time choice below, and registers the server with the Drive tools enabled. Manually:

git clone https://github.com/amgallego8/Colab-MCP ~/Colab-MCP && cd ~/Colab-MCP

uv sync uv run colab-cli-mcp-drive login # same login, run from the clone

login walks you through creating your own Google Cloud "Desktop app" client (about 10 minutes, once, free; steps below). When you give it the path of the JSON you downloaded it stores it for you (0600). You answer to Google for your project. After that, signing in is just: a link opens in your browser, you click Allow, done. There is no code to paste.

No shared one-click client is shipped yet. If this repository reaches 1,000 stars, the

Solo se muestra el principio; lee el resto en el repo

Colab-MCP (unofficial)

Resumen

Los tres pilares de PopNx MCP

Qué puedes hacer con él

Instalación

Antes de instalar

Valores que debes completar

Qué puede hacer

Revisiones básicasi

El creador coincide con el repo

Sigue en mantenimiento

Tiene licencia

El endpoint responde

Inicio de sesión con OAuth

Sin instrucciones ocultas en las descripciones de herramientas

Comparado con otros en Documentos, hojas de cálculo y oficinai

Preguntas frecuentes

Alternativas

Agent-Native Calendar

Excel MCP Server

MCP Server for Excel

README del creador

Colab-MCP

Quick start

Status

Tools (42 + 8 optional Drive tools)

Security model

Big projects and Drive on the VM

Where things live (and how little stays on your computer)

Google Drive: projects and notebooks (opt-in)

Who is responsible for what

Quick start (every user)