What does Cwprep do that alternatives don't?
Cwprep enables generation of Tableau Prep Flow (.tfl) files directly from natural language or Python code, acting as a bridge between LLMs and Tableau Prep without requiring the GUI.
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Basic information
ai generate tableau prep file
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"cwprep": {
"command": "uvx",
"args": [
"--from",
"cwprep[mcp]",
"cwprep-mcp"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
Fetch the live tool list by running this server in a temporary sandbox using the button above.
Cwprep is a Python-based engine that enables text-to-PrepFlow generation by reverse-engineering the .tfl JSON structure. It provides a built-in MCP server, acting as a bridge between LLMs (such as Claude and Gemini) and Tableau Prep, allowing users to generate, modify, and build data cleaning flows through natural language conversations or Python scripts without opening the GUI.
Install with pip install cwprep or use uvx (recommended) which auto-downloads the MCP extra. Start the MCP server locally with cwprep-mcp for stdio transport, or with cwprep-mcp --transport streamable-http --port 8000 for remote HTTP access. Configure supported clients (Claude Desktop, Cursor, VS Code, Windsurf, Gemini CLI, etc.) to point to this server using the uvx method.
.tflx archives with embedded data filesCwprep enables generation of Tableau Prep Flow (.tfl) files directly from natural language or Python code, acting as a bridge between LLMs and Tableau Prep without requiring the GUI.
Python 3.8 or higher is required. The MCP server extra can be installed via `pip install cwprep[mcp]` or auto-downloaded using `uvx`.
The server supports stdio transport (local) and Streamable HTTP transport (`--transport streamable-http --port 8000`). Authentication is not detailed in the README.
By default, the SDK and MCP output only the final `.tfl` or `.tflx` archive. Use `save_to_folder()` explicitly to obtain the exploded folder for inspection.
Yes, it supports database connections to MySQL, PostgreSQL, and SQL Server via `add_connection()`, with default settings configurable in `config.yaml`.

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