一个MCP服务器，用于程序化管理和交互Jupyter笔记本。

组成部分

工具

服务器提供六种笔记本操作工具：

1. read_notebook_with_outputs：读取笔记本内容，包括单元输出

• 必备：notebook_path（字符串）

2. read_notebook_source_only：读取笔记本内容，无需输出

• 必修：notebook_path（字符串）
• 当体积限制导致无法读取带输出的完整笔记本时使用

3. read_output_of_cell：读取特定单元的输出

• 必修：
• notebook_path（字符串）
• cell_id（字符串）

4. add_cell：向笔记本添加新单元格

• 必修：
• notebook_path（字符串）
• source（字符串）
• 可选：
• cell_type（字符串）：“代码”或“标记”
• position（整数）：插入索引（-1 用于附加）

5. edit_cell：修改现有细胞内容

• 必修：
• notebook_path（字符串）
• cell_id（字符串）：要编辑单元格的唯一ID
• source（字符串）

6. execute_cell：执行特定单元并返回其输出

• 必修：
• notebook_path（字符串）
• cell_id（弦）
• 用于验证单元的执行和输出

使用 Claude Desktop

mcp-server-jupyter

An MCP server for managing and interacting with Jupyter notebooks programmatically.

Components

Tools

The server provides six tools for notebook manipulation:

1. read_notebook_with_outputs: Read a notebook’s content including cell outputs

   • Required: notebook_path (string)

2. read_notebook_source_only: Read notebook content without outputs

   • Required: notebook_path (string)
   • Use when size limitations prevent reading full notebook with outputs

3. read_output_of_cell: Read output of a specific cell

   • Required:
     • notebook_path (string)
     • cell_id (string)

4. add_cell: Add new cell to notebook

   • Required:
     • notebook_path (string)
     • source (string)
   • Optional:
     • cell_type (string): “code” or “markdown”
     • position (integer): insertion index (-1 to append)

5. edit_cell: Modify existing cell content

   • Required:
     • notebook_path (string)
     • cell_id (string): Unique ID of the cell to edit
     • source (string)

6. execute_cell: Execute a specific cell and return its output

   • Required:
     • notebook_path (string)
     • cell_id (string)
   • Useful for verifying cell execution and output

Usage with Claude Desktop

Step1: Start JupyterLab or Jupyter Notebook

By using uv to run Jupyter notebooks it’s much easier to manage venv and package installations.

Follow uv jupyter docummentation for more details.

uv venv --seed
source .venv/bin/activate
uv pip install jupyterlab
.venv/bin/jupyter lab

NOTE: this environment should be used as UV_PROJECT_ENVIRONMENT env variable in MCP server (next step). Run in the same folder where Jupyter started.

echo $(pwd)/.venv

Step2: Configure Claude Desctop Add this configuration to your Claude Desktop config file:

PyPi package:

// ~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "Jupyter-notebook-manager": {
      "command": "uv",
      "args": ["run", "--with", "mcp-server-jupyter", "mcp-server-jupyter"],
      "env": {
        "UV_PROJECT_ENVIRONMENT": "/path/to/venv_for_jupyter/.venv"
      }
    }
  }
}

Git repo fork

// ~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "Jupyter-notebook-manager": {
      "command": "uv",
      "args": [
        "run",
        "--directory",
        "/Users/inna/mcp-server-jupyter/src/mcp_server_jupyter",
        "mcp-server-jupyter"
      ],
      "env": {
        "UV_PROJECT_ENVIRONMENT": "/path/to/venv_for_jupyter/.venv"
      }
    }
  }
}

Step 3: Open Notebook & Claude Chat

Open or create a notebook in JupyterLab/Jupyter Notebook

Get the full path to your notebook: