@ihrpr
基本信息
MCP server for Jupyter Notebooks and JupyterLab
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"mcp-server-jupyter": {
"command": "uv",
"args": [
"venv",
"--seed"
]
}
}
}`notebook_path` (string)
`notebook_path` (string)
`notebook_path` (string)
`notebook_path` (string)
`cell_type` (string): "code" or "markdown"
`notebook_path` (string)
`notebook_path` (string)
mcp-server-jupyter is an MCP server that enables programmatic management and interaction with Jupyter notebook files. It provides tools to read, edit, add, and execute cells within notebooks. It is intended for developers using AI assistants (like Claude) who need to manipulate Jupyter notebooks remotely.
Start JupyterLab in a uv-managed virtual environment, then add the server to your Claude Desktop configuration using uv run --with mcp-server-jupyter mcp-server-jupyter and set the UV_PROJECT_ENVIRONMENT env variable to that environment’s path. Provide the full notebook file path when calling tools.
Six tools: `read_notebook_with_outputs`, `read_notebook_source_only`, `read_output_of_cell`, `add_cell`, `edit_cell`, and `execute_cell`. Each requires the notebook file path; cell‑specific tools also need a cell ID.
You must have Python and `uv` installed. A JupyterLab instance must be running, and the `UV_PROJECT_ENVIRONMENT` environment variable must point to that instance’s virtual environment.
In JupyterLab: right‑click the notebook in the file browser and choose “Copy Path”. In Jupyter Notebook: copy the path from the URL and modify it to a full system path. Always use the full path when calling tools.
No. After using `add_cell` or `edit_cell`, you must manually reload the notebook page in JupyterLab/Jupyter Notebook to see the modifications.
The server communicates via standard MCP transport (stdio). No authentication configuration is described; it relies on the local filesystem and the running Jupyter instance.
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