test-tableau-mcp
About
a quick POC to expose Tableau VDS endpoints through an MCP server and integrate them with Claude Desktop client
Details
- Author
- joeconstantino
- GitHub stars
- 3
- Downloads
- 226
- Categories
- Search
Jump to
- Exposes Tableau VDS API as MCP tools.
- Query data sources with fields, filters, sorts, and limits.
- Integrates directly with Claude Desktop.
- Supports in-context sample payloads for correct syntax.
- Requires manual authentication via hardcoded session token.
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
test-tableau-mcpCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Set up a Python environment with UV, hardcode four variables (server URL, metadata GraphQL URL, datasource LUID, and session token) in vds.py, then run the server with uv --directory <ABSOLUTE PATH> run vds.py. Configure Claude Desktop by adding the server to its claude_desktop_config.json and restart the app.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"test-tableau-mcp": {
"vds": {
"command": "uv",
"args": [
"--directory",
"/ABSOLUTE/PATH/TO/PARENT/FOLDER/test-tableau-mcp/",
"run",
"vds.py"
]
}
}
}
}McpServers
{
"vds": {
"command": "uv",
"args": [
"--directory",
"/ABSOLUTE/PATH/TO/PARENT/FOLDER/test-tableau-mcp/",
"run",
"vds.py"
]
}
}test-tableau-mcp
This project is a quick prototype to expose Tableau VDS endpoints through an MCP server and integrate them with Claude Desktop client.To run this MCP Server and connect it Claude Desktop follow these steps. These instructions were adapted from the MCP how-to guide. These instructions assume you are using MacOS/Linux. If you're running Windows, refer to the how-to guide linked above.
System requirements
Python 3.10 or higher installed. You must use the Python MCP SDK 1.2.0 or higher.Set up your environment
Install UV if you haven't already.curl -LsSf https://astral.sh/uv/install.sh | sh
Now, create and set up your virtual environment:
```python
Sign in to leave a review
Use Google, GitHub, or an email account so ratings stay tied to real people.
No reviews posted yet.
