Data Processing

Jupyter Notebook to Reproducible Script Linearizer

Turn .ipynb into a # %% Python script and detect out-of-order, hidden, and deleted state

text· Text resultOpen tool

Quick start

Call this tool from your code in three languages.

cURL

# 1) Request a presigned URL → returns { uploadUrl, storageKey }
curl -X POST 'https://api.elysiatools.com/api/upload/presign/jupyter-notebook-to-reproducible-script-linearizer' \
  -H 'Content-Type: application/json' \
  -d '{"filename":"notebookFile.ext","contentType":"application/octet-stream","size":12345}'

# 2) PUT the file bytes directly to the presigned uploadUrl
curl -X PUT '<presigned uploadUrl>' \
  --data-binary @/path/to/file.ext

# 3) Call the tool, passing the returned storageKey for each file field
curl -X POST 'https://api.elysiatools.com/en/api/tools/jupyter-notebook-to-reproducible-script-linearizer' \
  -F 'notebookInput={"nbformat":4,"cells":[{"cell_type":"code","execution_count":2,"source":["print(model)"]},{"cell_type":"code","execution_count":1,"source":["import numpy as np\nmodel = np.random.rand(3)"]}]}' \
  -F 'notebookFile=uploads/2026/01/01/your-tool-1700000000000-abc123.ext' \
  -F 'cellOrder=execution' \
  -F 'includeMarkdown=true'

API reference

Send a POST request with your inputs as JSON. File parameters require a separate upload first.

Endpoint

HTTP

POST https://api.elysiatools.com/en/api/tools/jupyter-notebook-to-reproducible-script-linearizer

Parameters

Name	Type	Required	Description
notebookInput	textarea	No	—
notebookFile	fileupload required	No	—
cellOrder	select	No	—
includeMarkdown	checkbox	No	—

File-type parameters must be uploaded first via POST /upload/jupyter-notebook-to-reproducible-script-linearizer, then the returned filePath is passed to the corresponding file field.

Response format

Text result

JSON

{
  "result": "Processed text content",
  "error": "Error message (optional)",
  "message": "Notification message (optional)",
  "metadata": {
    "key": "value"
  }
}

MCP integration

Add this tool to your Model Context Protocol server so AI agents can list and call it.

Server configuration

Add this block to your MCP client configuration:

mcp.json

{
  "mcpServers": {
    "elysiatools-jupyter-notebook-to-reproducible-script-linearizer": {
      "name": "jupyter-notebook-to-reproducible-script-linearizer",
      "description": "Turn .ipynb into a # %% Python script and detect out-of-order, hidden, and deleted state",
      "baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=jupyter-notebook-to-reproducible-script-linearizer",
      "command": "",
      "args": [],
      "env": {},
      "isActive": true,
      "type": "sse"
    }
  }
}

List available tools

After connecting to the SSE endpoint, list the exposed tools:

tools/list

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/list"
}

Call this tool

Invoke the tool by its id, passing arguments built from its parameters:

tools/call

{
  "jsonrpc": "2.0",
  "id": 2,
  "method": "tools/call",
  "params": {
    "name": "jupyter-notebook-to-reproducible-script-linearizer",
    "arguments": {
  "notebookInput": "{\"nbformat\":4,\"cells\":[{\"cell_type\":\"code\",\"execution_count\":2,\"source\":[\"print(model)\"]},{\"cell_type\":\"code\",\"execution_count\":1,\"source\":[\"import numpy as np\\nmodel = np.random.rand(3)\"]}]}",
  "notebookFile": "https://example.com/file.ext",
  "cellOrder": "execution",
  "includeMarkdown": true
}
  }
}

Chain multiple tools in one session with a comma-separated toolId list, e.g. /mcp/sse?toolId=png-to-webp,jpg-to-webp,gif-to-webp (max 20).

File parameters accept a public file URL only (https://…). Local paths, data: URIs, and Base64 strings are not supported.

Questions or issues? Contact [email protected]