MCP Jupyter Complete MCP Server

Complete MCP server for Jupyter notebook manipulation with position-based operations and VS Code integration

Local serverstdioPython

What is the MCP Jupyter Complete MCP server?

Complete MCP server for Jupyter notebook manipulation with position-based operations and VS Code integration. Exposed over MCP by the mcp jupyter complete mcp server, that capability becomes something an assistant can invoke while it works, not something you go and do afterwards.

Adding it to your client

Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client. The configuration blocks on this page cover the common clients.

Its toolset

Everything the assistant can do here goes through one of these:

  • Function — Parameters
  • list_cells — notebook_path
  • get_cell_source — notebook_path, cell_index
  • edit_cell_source — notebook_path, cell_index, new_source
  • insert_cell — notebook_path, position, cell_type?, source?
  • delete_cell — notebook_path, cell_index
  • move_cell — notebook_path, from_index, to_index
  • convert_cell_type — notebook_path, cell_index, new_type
  • bulk_edit_cells — notebook_path, operations[]
  • trigger_vscode_reload — notebook_path
  • Testing — The Testing tool exposed by this server
  • Linting — The Linting tool exposed by this server

Caveats

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • With 12 tools registered it takes up a noticeable share of the context window; turn it off in projects that never touch MCP Jupyter Complete.
  • MCP clients confirm each tool call by default. Leave that on until you have watched what the mcp jupyter complete mcp server does with a few real requests.

When to reach for it

Plenty of developer tooling servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. MCP Jupyter Complete's toolset — Function, list_cells, get_cell_source and 9 more — is a fair guide to whether it matches your workflow. It is maintained by tofunori; worth a glance at recent repository activity before you build anything load-bearing on it.

SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.

Available tools

ToolWhat it does
FunctionParameters
list_cellsnotebook_path
get_cell_sourcenotebook_path, cell_index
edit_cell_sourcenotebook_path, cell_index, new_source
insert_cellnotebook_path, position, cell_type?, source?
delete_cellnotebook_path, cell_index
move_cellnotebook_path, from_index, to_index
convert_cell_typenotebook_path, cell_index, new_type
bulk_edit_cellsnotebook_path, operations[]
trigger_vscode_reloadnotebook_path
TestingThe Testing tool exposed by this server.
LintingThe Linting tool exposed by this server.

How to install the MCP Jupyter Complete MCP server

Or if installed globally via npm:

```json
{
  "mcpServers": {
    "jupyter-complete": {
      "command": "mcp-jupyter-complete"
    }
  }
}

Configuration as documented by the project. Restart the client after saving.

Example prompts to try

  • Use MCP Jupyter Complete to Function.
  • Use MCP Jupyter Complete to list cells.
  • Use MCP Jupyter Complete to get cell source.

Frequently asked questions

It connects MCP Jupyter Complete to MCP-compatible AI assistants such as Claude and Cursor, exposing 12 tools (Function, list_cells, get_cell_source, and more) that the assistant can call on your behalf. Instead of copying data back and forth by hand, the assistant works with MCP Jupyter Complete directly.