execute_cell - Jupyter MCP Server

Execute a cell from the currently activated notebook with timeout and return it's outputs

destructive: yes · idempotent: no · open-world: yes

Parameters

Parameter	Type	Required	Default	Description
`cell_index`	integer \| null	no	`null`	Index of the cell to execute (0-based). Omit when passing cell_id.
`timeout`	integer	no	`0`	Maximum seconds to wait for execution (0 = use config default)
`stream`	boolean	no	`true`	Enable streaming progress (including time indicator) updates for long-running cells
`progress_interval`	integer	no	`5`	Seconds between progress updates (MCP keepalive + optional stream log)
`cell_id`	string \| null	no	`null`	Address the cell by its notebook cell id instead of its index. An index is a position, and a position stops being true the moment anyone inserts a cell above it; an id does not. Every result says which id it acted on, so read a cell once and address it by id afterwards. Given both, the id wins.

Output

{
  "properties": {
    "kind": {
      "description": "What this result is — 'cell.read', 'notebooks.list' and so on. Lets a client tell one answer from another without matching prose.",
      "title": "Kind",
      "type": "string"
    },
    "result": {
      "default": null,
      "description": "The answer itself: a message, the rows of a listing, or the outputs of an execution in order.",
      "title": "Result"
    },
    "outputs": {
      "description": "The outputs in order: text as text, an image as its own object.",
      "items": {},
      "title": "Outputs",
      "type": "array"
    },
    "count": {
      "default": 0,
      "description": "How many outputs.",
      "title": "Count",
      "type": "integer"
    },
    "images": {
      "default": 0,
      "description": "How many of them are images.",
      "title": "Images",
      "type": "integer"
    }
  },
  "required": [
    "kind"
  ],
  "type": "object",
  "additionalProperties": true,
  "description": "Cell or execution outputs, in order.",
  "title": "OutputsAnswer"
}

Call it

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "execute_cell",
    "arguments": {
      "cell_index": null,
      "timeout": 0,
      "stream": true,
      "progress_interval": 5,
      "cell_id": null
    }
  }
}

result = await session.call_tool("execute_cell", arguments={"cell_index": None, "timeout": 0, "stream": True, "progress_interval": 5, "cell_id": None})

Source

Registered by the @mcp.tool decorator on execute_cell in jupyter_mcp_server/server.py.