Jupyter 노트북 프로그래밍과 상호 작용하는 MCP 서버.

부품

도구

서버는 노트북 조작을 위한 6개의 공구를 제공합니다:

1. read_notebook_with_outputs : 셀 출력을 포함한 노트북의 콘텐츠를 읽으십시오.

• 필수 : notebook_path (문자)

2. read_notebook_source_only: 출력 없이 노트북 내용 읽기

• 필수 : [T3]] (문자)
• 크기 제한이 출력을 가진 가득 차있는 노트북을 읽는 것을 방지할 때 사용

3. [T4]]: 특정 셀의 출력 읽기

• 필수 :
• [T5]] (문자)
• [T6]] (문자)

4. [T7]]: 노트북에 새로운 세포를 추가

• 필수 :
• [T8]] (문자)
• [T9]] (문자)
• 선택:
• cell_type (string): “코드” 또는 “markdown”
• position (integer): 삽입 색인 (-1 에 append)

5. [T12]]: 기존 셀 콘텐츠 수정

• 필수 :
• [T13]] (문자)
• cell_id (string): 세포의 고유 ID를 편집
• [T15]] (문자)

6. [T16]]: 특정 셀을 실행하고 출력을 반환

• 필수 :
• [T17]] (문자)
• [T18]] (문자)
• 셀 실행 및 출력 확인에 유용한

Claude 데스크탑 사용

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: