Colab MCP
Connects local AI assistants directly to browser-based Google Colab notebooks, enabling execution of Python code and interaction with notebook states.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Colab MCP run this pandas code to analyze the dataset"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
πͺ Colab MCP (Model Context Protocol)
An MCP (Model Context Protocol) server that seamlessly bridges your local AI agent to a Google Colab session running in your browser.
β¨ Features
Connects local AI assistants directly to browser-based Colab notebooks
Supports executing Python code in Colab via the agent
Reads and interacts with Colab notebook states
Related MCP server: colab-mcp
π» Supported Clients
This MCP server requires a client that supports notifications/tools/list_changed and must be running locally on your device.
Popular clients that meet these criteria include:
π Installation & Setup
Install
uv(an extremely fast Python package installer and resolver):pip install uvConfigure your MCP Client (e.g., in your
mcp.jsonor equivalent configuration file):{ "mcpServers": { "colab-mcp": { "command": "uvx", "args": ["git+https://github.com/googlecolab/colab-mcp"], "timeout": 30000 } } }Note for Googlers (or those with non-standard package indexes): You may need to add
--index https://pypi.org/simpleto theargsarray.
π¬ Issues & Discussions
We use GitHub Discussions as our primary venue for issue discussion and feature requests.
As discussions mature into clear action items, the maintainers will convert them into tracked issues. This workflow helps us ensure that the issue tracker remains deduplicated, well-understood, and highly actionable.
β οΈ Please do NOT open issues directly.
π€ Contributing
While we appreciate community interest, we currently do not have the bandwidth to review external contributions. We want to avoid user Pull Requests languishing without review, so we are not accepting external contributions at this time.
If you have a great idea or encounter a pain point, we would love to hear about it on our Discussions page!
π οΈ Internal (For Colab Developers)
Prerequisites
uvis required (pip install uv)Configure git hooks to run repository presubmits:
git config core.hooksPath .githooks
Local Development Setup (Gemini CLI)
To test your local checkout with the Gemini CLI, use this configuration:
{
"mcpServers": {
"colab-mcp": {
"command": "uv",
"args": ["run", "colab-mcp"],
"cwd": "/path/to/github/colab-mcp",
"timeout": 30000
}
}
}MCP_Colab
Available Tools
1 toolopen_colab_browser_connectionA
Opens a connection to a Google Colab browser session and unlocks notebook editing tools. Returns a boolean representing whether the connection attempt succeeded
Inputs: no named parameters. Returns: result
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelogβ¦
TDQS
Scored across 1 tool
Only one tool exists, so no ambiguity between tools, but the dimension assesses whether tools can be told apart; with one tool there is no need for disambiguation, but it cannot be 'clearly distinct' from others since there are none.
With a single tool, naming consistency is not applicable; however, the name is descriptive and follows a reasonable pattern, so a neutral score is given.
A single tool seems too few for a server named 'Colab MCP', which suggests a broader purpose. The tool only handles opening a connection, leaving other expected functionalities uncovered.
The server's domain appears to be Google Colab integration, but only one tool for opening a connection is provided. Missing tools for editing, running cells, managing notebooks, etc., make the surface severely incomplete.
Maintenance
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