Cwprep

cwprep is a Python-based engine that enables Text-to-PrepFlow generation.

By reverse-engineering the .tfl JSON structure and providing a built-in MCP (Model Context Protocol) server, cwprep acts as a bridge between LLMs (like Claude, Gemini) and Tableau Prep. You can now generate, modify, and build data cleaning flows simply through natural language conversations or Python scripts, without ever opening the GUI!

Author: Cooper Wenhua <[email protected]>

Installation

pip install cwprep

Quick Start

from cwprep import TFLBuilder, TFLPackager

# Create builder
builder = TFLBuilder(flow_name="My Flow")

# Add database connection
conn_id = builder.add_connection(
    host="localhost",
    username="root",
    dbname="mydb"
)

# Add input tables
orders = builder.add_input_table("orders", "orders", conn_id)
customers = builder.add_input_table("customers", "customers", conn_id)

# Join tables
joined = builder.add_join(
    name="Orders + Customers",
    left_id=orders,
    right_id=customers,
    left_col="customer_id",
    right_col="customer_id",
    join_type="left"
)

# Add output
builder.add_output_server("Output", joined, "My_Datasource")

# Build and save
flow, display, meta = builder.build()
TFLPackager.save_tfl("./my_flow.tfl", flow, display, meta)

By default, both the SDK and MCP output only the final .tfl/.tflx archive. Use save_to_folder() only when you explicitly want the exploded folder for inspection.

Features

Examples

See the examples/ directory for complete demos:

• demo_basic.py - Input, Join, Output
• demo_cleaning.py - Filter, Calculate, Rename
• demo_field_operations.py - Quick Calc, Change Type, Duplicate Column
• demo_aggregation.py - Union, Aggregate, Pivot
• demo_comprehensive.py - All features combined
• prompts.md - 8 ready-to-use MCP prompt templates for AI-driven flow generation

MCP Server

cwprep includes a built-in Model Context Protocol server, enabling AI clients (Claude Desktop, Cursor, Gemini CLI, etc.) to generate TFL files directly.

Prerequisites

Quick Start

# Local (stdio)
cwprep-mcp

# Remote (Streamable HTTP)
cwprep-mcp --transport streamable-http --port 8000

[!TIP] Upgrading? If you previously used uvx with an older version, clear the cache to pick up the latest release:

uv cache clean cwprep

Client Configuration

All clients below use the uvx method (recommended). Replace uvx with cwprep-mcp if you prefer a local pip install.

{
  "mcpServers": {
    "cwprep": {
      "command": "uvx",
      "args": ["--from", "cwprep[mcp]", "cwprep-mcp"]
    }
  }
}

{
  "mcpServers": {
    "cwprep": {
      "command": "uvx",
      "args": ["--from", "cwprep[mcp]", "cwprep-mcp"]
    }
  }
}

{
  "servers": {
    "cwprep": {
      "command": "uvx",
      "args": ["--from", "cwprep[mcp]", "cwprep-mcp"]
    }
  }
}

{
  "mcpServers": {
    "cwprep": {
      "command": "uvx",
      "args": ["--from", "cwprep[mcp]", "cwprep-mcp"]
    }
  }
}

claude mcp add cwprep -- uvx --from "cwprep[mcp]" cwprep-mcp

{
  "mcpServers": {
    "cwprep": {
      "command": "uvx",
      "args": ["--from", "cwprep[mcp]", "cwprep-mcp"]
    }
  }
}

mcpServers:
  - name: cwprep
    command: uvx
    args:
      - --from
      - cwprep[mcp]
      - cwprep-mcp

cwprep-mcp --transport streamable-http --port 8000

Available MCP Capabilities

AI Skill Support

This project includes a specialized AI Skill for assistants like Claude or Gemini to help you build flows.

• Location: .agents/skills/tfl-generator/
• Features: MCP server index with fallback SDK usage guide. Detailed API and syntax references are served via MCP Resources from src/cwprep/references/.

Directory Structure

cwprep/
├── .agents/skills/      # AI Agent skills (MCP index)
├── src/cwprep/          # SDK source code
│   ├── builder.py       # TFLBuilder class
│   ├── packager.py      # TFLPackager class
│   ├── translator.py    # SQLTranslator class
│   ├── expression_translator.py  # ExpressionTranslator class
│   ├── config.py        # Configuration utilities
│   ├── mcp_server.py    # MCP Server (Tools, Resources, Prompts)
│   └── references/      # MCP Resource documents (.md)
├── examples/            # Demo scripts
├── docs/                # Documentation
└── tests/               # Unit tests

Configuration

Create config.yaml for default settings:

# MySQL (default)
database:
  host: localhost
  port: 3306
  dbname: mydb
  type: mysql

# SQL Server (Windows Authentication)
# database:
#   host: localhost
#   type: sqlserver
#   authentication: sspi
#   schema: dbo

# PostgreSQL
# database:
#   host: localhost
#   port: 5432
#   dbname: mydb
#   type: postgres

tableau_server:
  url: http://your-server
  default_project: Default

Changelog

See changelog.md for version history.

License

AGPL-3.0 License