Colab MCP
🪐 Colab MCP (模型上下文协议)
一个 MCP (模型上下文协议) 服务器,可将您的本地 AI 智能体无缝连接到浏览器中运行的 Google Colab 会话。
✨ 功能
将本地 AI 助手直接连接到基于浏览器的 Colab 笔记本
支持通过智能体在 Colab 中执行 Python 代码
读取并与 Colab 笔记本状态进行交互
Related MCP server: colab-mcp
💻 支持的客户端
此 MCP 服务器需要一个支持 notifications/tools/list_changed 且必须在您的设备上本地运行的客户端。
符合这些条件的常用客户端包括:
🚀 安装与设置
安装
uv(一个速度极快的 Python 包安装程序和解析器):pip install uv配置您的 MCP 客户端 (例如,在您的
mcp.json或等效配置文件中):{ "mcpServers": { "colab-mcp": { "command": "uvx", "args": ["git+https://github.com/googlecolab/colab-mcp"], "timeout": 30000 } } }谷歌员工(或使用非标准包索引的用户)请注意: 您可能需要在
args数组中添加--index https://pypi.org/simple。
💬 问题与讨论
我们使用 GitHub Discussions 作为我们讨论问题和功能请求的主要场所。
当讨论成熟为明确的行动项时,维护者会将其转换为跟踪问题。此工作流程有助于我们确保问题跟踪器保持去重、易于理解且具有高度可操作性。
⚠️ 请不要直接提交 issue。
🤝 贡献
虽然我们感谢社区的关注,但我们目前没有足够的带宽来审查外部贡献。我们希望避免用户的 Pull Request 因缺乏审查而搁置,因此我们目前不接受外部贡献。
如果您有好的想法或遇到痛点,我们非常乐意在我们的 Discussions 页面上听到您的声音!
🛠️ 内部(供 Colab 开发人员使用)
先决条件
需要
uv(pip install uv)配置 git 钩子以运行存储库预提交检查:
git config core.hooksPath .githooks
本地开发设置 (Gemini CLI)
要使用 Gemini CLI 测试您的本地检出版本,请使用以下配置:
{
"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 changelog…
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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