U
UsamaK98/python-notebook-mcp
Create and edit Jupyter notebooks
在 GitHub 查看 ↗链接已于 2026-11-12 核查 · HTTP 200 · 打开的是厂商自己的官网
安装与配置
取自该仓库的安装命令
pip install fastmcp
解析自我们于 2026-11-07 抓取的该仓库 README;我们未执行过。
这条是仓库自己写的安装方式,不是 MCP 客户端配置,所以不生成 JSON。
配置项的键名以你的客户端为准:客户端与 CLI
- 来源明细
- 收录自 abordage/awesome-mcp 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
- 收录与活跃
- 收录于 2026-11-05 · 最近见到 2026-11-14 · 共见到 10 次 · 被 10 个来源列出
- 评分构成
- 综合分 1,003 · 10 个来源 · mcp
- 安装
pip install fastmcp
常见问题(答案都来自我们的记录)
怎么安装?
该仓库给出的安装命令是
pip install fastmcp。我们的记录里它是仓库自己提供的;不保证在你的客户端上直接可用。它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
我们收录于 2026-11-05;最近见到 2026-11-14。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
Python Notebook MCP
以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →
MCP server enabling AI assistants to interact with Jupyter notebooks through the Model Context Protocol.
This server allows compatible AI assistants (like Cursor or Claude Desktop) to interact with Jupyter Notebook files (.ipynb) on your local machine.
## 📋 Prerequisites
Before you begin, ensure you have the following installed:
1. Python: Version 3.10 or higher.
2. uv: The fast Python package installer and virtual environment manager from Astral. If you don't have it, install it:
bash
# On macOS / Linux
curl -LsSf https://astral.sh/uv/install.sh | sh
# On Windows (PowerShell)
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"
# IMPORTANT: Add uv to your PATH if prompted by the installer
# For macOS/Linux (bash/zsh), add to your ~/.zshrc or ~/.bashrc:
# export PATH="$HOME/.local/bin:$PATH"
# Then restart your shell or run source ~/.zshrc (or equivalent)
3. fastmcp CLI (Optional, for Claude Desktop fastmcp install): If you plan to use the fastmcp install method for Claude Desktop, you need the fastmcp command available.
bash
# Using uv
uv pip install fastmcp
# Or using pipx (recommended for CLI tools)
pipx install fastmcp
## 🔧 Setup
1. Clone the Repository:
bash
git clone https://github.com/UsamaK98/python-notebook-mcp.git # Or your fork/local path
cd python-notebook-mcp
2. Choose Setup Method:
Option A: Automated Setup (Recommended)
Run the appropriate script for your OS from the project's root directory (where you just cd-ed into).
macOS / Linux:
bash
# Make script executable (if needed)
chmod +x ./install_unix.sh
# Run the script
bash ./install_unix.sh
Windows (PowerShell):
powershell
# You might need to adjust PowerShell execution policy first
# Set-ExecutionPolicy RemoteSigned -Scope CurrentUser
.\install_windows.ps1
These scripts will create the .venv, install dependencies, and output the exact paths needed for your MCP client configuration.
Option B: Manual Setup
Follow these steps if you prefer manual control or encounter issues with the scripts.
1. Create & Activate Virtual Environment:
bash
# Create the environment (e.g., named .venv)
uv venv
# Activate the environment
# On macOS/Linux (bash/zsh):
source .venv/bin/activate
# On Windows (Command Prompt):
# .venv\Scripts\activate.bat
# On Windows (PowerShell):
# .venv\Scripts\Activate.ps1
(You should see (.venv) or similar at the start of your shell prompt)
2. Install Dependencies:
bash
# Make sure your venv is active
uv pip install -r requirements.txt
## ▶️ Running the Server
Make sure your virtual environment (.venv) is activated if you used manual setup.
### Method 1: Direct Execution (Recommended for Cursor, General Use)
This method uses uv run to execute the server script directly using your current Python environment (which should now have the dependencies installed).
1. Run the Server:
bash
# From the python-notebook-mcp directory
uv run python server.py
The server will start and print status messages, including the (uninitialized) workspace directory.
2. Client Configuration (mcp.json): Configure your MCP client (e.g., Cursor) to connect. Create or edit the client's MCP configuration file (e.g., .cursor/mcp.json in your workspace).
Template (Recommended):
json
This server allows compatible AI assistants (like Cursor or Claude Desktop) to interact with Jupyter Notebook files (.ipynb) on your local machine.
## 📋 Prerequisites
Before you begin, ensure you have the following installed:
1. Python: Version 3.10 or higher.
2. uv: The fast Python package installer and virtual environment manager from Astral. If you don't have it, install it:
bash
# On macOS / Linux
curl -LsSf https://astral.sh/uv/install.sh | sh
# On Windows (PowerShell)
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"
# IMPORTANT: Add uv to your PATH if prompted by the installer
# For macOS/Linux (bash/zsh), add to your ~/.zshrc or ~/.bashrc:
# export PATH="$HOME/.local/bin:$PATH"
# Then restart your shell or run source ~/.zshrc (or equivalent)
3. fastmcp CLI (Optional, for Claude Desktop fastmcp install): If you plan to use the fastmcp install method for Claude Desktop, you need the fastmcp command available.
bash
# Using uv
uv pip install fastmcp
# Or using pipx (recommended for CLI tools)
pipx install fastmcp
## 🔧 Setup
1. Clone the Repository:
bash
git clone https://github.com/UsamaK98/python-notebook-mcp.git # Or your fork/local path
cd python-notebook-mcp
2. Choose Setup Method:
Option A: Automated Setup (Recommended)
Run the appropriate script for your OS from the project's root directory (where you just cd-ed into).
macOS / Linux:
bash
# Make script executable (if needed)
chmod +x ./install_unix.sh
# Run the script
bash ./install_unix.sh
Windows (PowerShell):
powershell
# You might need to adjust PowerShell execution policy first
# Set-ExecutionPolicy RemoteSigned -Scope CurrentUser
.\install_windows.ps1
These scripts will create the .venv, install dependencies, and output the exact paths needed for your MCP client configuration.
Option B: Manual Setup
Follow these steps if you prefer manual control or encounter issues with the scripts.
1. Create & Activate Virtual Environment:
bash
# Create the environment (e.g., named .venv)
uv venv
# Activate the environment
# On macOS/Linux (bash/zsh):
source .venv/bin/activate
# On Windows (Command Prompt):
# .venv\Scripts\activate.bat
# On Windows (PowerShell):
# .venv\Scripts\Activate.ps1
(You should see (.venv) or similar at the start of your shell prompt)
2. Install Dependencies:
bash
# Make sure your venv is active
uv pip install -r requirements.txt
## ▶️ Running the Server
Make sure your virtual environment (.venv) is activated if you used manual setup.
### Method 1: Direct Execution (Recommended for Cursor, General Use)
This method uses uv run to execute the server script directly using your current Python environment (which should now have the dependencies installed).
1. Run the Server:
bash
# From the python-notebook-mcp directory
uv run python server.py
The server will start and print status messages, including the (uninitialized) workspace directory.
2. Client Configuration (mcp.json): Configure your MCP client (e.g., Cursor) to connect. Create or edit the client's MCP configuration file (e.g., .cursor/mcp.json in your workspace).
Template (Recommended):
json
收录徽章(可选)
想把收录标记放进 README 就复制这行,可选,不影响收录。
[](https://anclum.com/zh/s/usamak98-python-notebook-mcp/)
- 来源
- awesome · https://github.com/UsamaK98/python-notebook-mcp
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