colab-mcp
OfficialClick on "Install 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-mcpRun a Python cell in Colab that prints 'Hello World'"
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.
Colab-mcp
An MCP server for bridging your local agent to a Colab session in the browser.
Supported Clients
This MCP server requires client support for notifications/tools/list_changed and for the client to be running locally on your device.
Popular clients that fit these criteria include:
Gemini CLI
Claude Code
Windsurf
Setup
Install
uv(pip install uv)Configure for usage (eg for mcp.json style services):
...
"mcpServers": {
"colab-mcp": {
"command": "uvx",
"args": ["git+https://github.com/googlecolab/colab-mcp"],
"timeout": 30000
}
}
...(If you have a non-standard default package index (Googlers), you may also need to add --index https://pypi.org/simple)
Issues & Discussions
We are using GitHub discussions as the place for issue discussion and feature requests. As discussions mature into action items, we will add those items as issues. This helps us ensure that issues in the issue tracker are well-understood, deduplicated, and actionable. For these reasons, please do NOT open issues directly.
Contributing
We unfortunately don't have the bandwidth to support review of external contributions, and we don't want user PRs to languish, so we aren't accepting any external contributions right now.
If you have a great idea or pain point, we would love to hear about it on our discussions page - the preferred place for issue discussion and feature requests.
Internal - For Colab Developers
Prerequisites
uvis required (pip install uv)Configure git hooks to run repo presubmits
git config core.hooksPath .githooksGemini CLI setup
...
"mcpServers": {
"colab-mcp": {
"command": "uv",
"args": ["run", "colab-mcp"],
"cwd": "/path/to/github/colab-mcp",
"timeout": 30000
}
}
...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
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description adequately states the action and return value, but lacks details on side effects, required permissions, or error conditions. For a simple tool with no parameters, this is acceptable but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is highly concise: two clear sentences with no extraneous information. Front-loaded with the action, followed by return value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no parameters and no siblings, the description covers the core action and return value. It could mention potential prerequisites or side effects, but overall it is fairly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so schema coverage is 100%. The description adds no parameter-level meaning, which is appropriate given the empty input schema. Baseline score applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the action ('opens a connection') and the resource ('Google Colab browser session'), with a specific verb and resource, and mentions the return value. No siblings exist, so no differentiation needed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. The description does not mention prerequisites, context, or conditions for invocation, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
1 tool update
v1.0.1- First observed
open_colab_browser_connection
TDQS
Only one tool exists, so there is no risk of confusion or overlap with other tools.
The single tool name follows a clear verb_noun pattern ('open_colab_browser_connection'), so consistency is not an issue.
A single tool is too few for a server intended to enable Colab notebook editing; the tool merely opens a connection, suggesting many necessary actions are missing.
The tool set is severely incomplete: it only provides a connection opener and lacks any tools for actual notebook editing, despite claiming to unlock such tools.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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