Tableau MCP

Organization

tableau

Tableau's official MCP Server. Helping Agents see and understand data.

Publisher	tableau
Repository	`tableau-mcp`
Language	TypeScript
Forks	103
Stars	269
Available tools	16
Transport type	stdio
Categories	Other
License	Apache-2.0
Links	GitHub Homepage

Connect tools to AI workflows
Tableau MCP exposes MCP capabilities that can be used by compatible AI clients and agents.
16 available tools
Browse the callable actions below, including names and descriptions when provided by the server.
Ready-to-copy setup
Use the installation snippets to configure this server in your preferred MCP client.
Open source signals
269 stars and 103 forks from the linked repository.

Tableau MCP

Overview

Tableau MCP is a suite of developer primitives, including tools, resources and prompts, that will make it easier for developers to build AI applications that integrate with Tableau.

Official Documentation

https://tableau.github.io/tableau-mcp/

Quick Start

Requirements

Node.js 22.7.5 or newer
An MCP client e.g. Claude Desktop, Cursor, VS Code, MCP Inspector, etc.

Standard config works in most MCP clients:

json
{
  "mcpServers": {
    "tableau": {
      "command": "npx",
      "args": ["-y", "@tableau/mcp-server@latest"],
      "env": {
        "SERVER": "https://my-tableau-server.com",
        "SITE_NAME": "my_site",
        "PAT_NAME": "my_pat",
        "PAT_VALUE": "pat_value"
      }
    }
  }
}

Deploy to Heroku

Example Prompts to Client

Prompt #1: Querying Data


For the Superstore Datasource, what are the top 5 states with the most sales in 2025?

Response


Based on the Superstore Datasource, here are the top 5 states with the most sales in 2025:
  1. California - $146,388.34
  2. New York - $93,922.99
  3. Washington - $65,539.90
  4. Texas - $43,421.76
  5. Pennsylvania - $42,688.31
California leads by a significant margin with over $146,000 in sales, followed by New York with nearly $94,000. These two states alone account for a substantial portion of the total sales across the top 5 states.

Prompt #2: Content Exploration


Find me the most viewed workbook within the last year.

Response


The most viewed workbook within the last year is:

Global Connections
- Owner: John Doe
- Project: Marketing
- Views in last year: 523
- Last Modified: September 2, 2025
- Workbook ID: 111fb672-9401-4913-a167-17b3d89a3e4f

Prompt #3: Getting a View


Show me an image of the "Economy" view in the "Finances" project.

Response

Economy View Image

Installation

TypingMind

Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "tableau": {
      "command": "npx",
      "args": [
        "-y",
        "@tableau/tableau-mcp"
      ],
      "env": {
        "TABLEAU_SERVER": "<YOUR_TABLEAU_SERVER>",
        "TABLEAU_PAT_NAME": "<YOUR_PAT_NAME>",
        "TABLEAU_PAT_VALUE": "<YOUR_PAT_VALUE>"
      }
    }
  }
}

Available Tools

query_data_source
Execute VizQL queries against connected data sources using natural language
list_workbooks
Retrieve a list of available workbooks on the Tableau server
get_workbook_metadata
Get detailed metadata for a specific workbook including sheets, data sources, and fields
create_worksheet
Create a new worksheet in a workbook with specified visualizations and data
update_dashboard
Modify an existing dashboard by adding, removing, or updating visualizations
list_data_sources
Get all available data sources and their connection details
get_data_source_schema
Retrieve schema information including fields, data types, and relationships for a data source
create_calculated_field
Define and create new calculated fields using Tableau calculations
generate_visualization
Create visualizations from data using natural language descriptions
publish_workbook
Publish a workbook to Tableau Server or Tableau Cloud
get_view_data
Extract underlying data from a specific view or visualization
create_data_extract
Generate Tableau data extracts (.hyper files) from connected data sources
refresh_data_source
Trigger a refresh of live data connections or extracts
apply_filters
Add or modify filters on worksheets and dashboards programmatically
export_view
Export views and dashboards in various formats (PDF, PNG, CSV, etc.)
get_server_info
Retrieve Tableau Server information including version, sites, and permissions

Use Tableau MCP MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once Tableau MCP is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

Open TypingMind in your browser.
Click the Settings icon.
Go to Advanced Settings.
Open the Model Context Protocol section.
Click Setup Connector and choose This Device.

TypingMind MCP connector setup screen with This Device selected

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

Copy the setup command shown by TypingMind.
Open Terminal on macOS or Windows Terminal on Windows.
Paste and run the command.
Approve the package install if Terminal asks you to proceed.
Keep the Terminal window running while using MCP tools.

Add Tableau MCP as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

Wait until the connector status shows Ready.
Click Edit Servers.
Paste the Tableau MCP MCP server configuration.
Save the server list.
Refresh if you want to confirm the connector is still ready.

TypingMind MCP settings showing active server and Edit Servers button

Use it across models

Save the server list, open Plugins, enable the Tableau MCP MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

Open the Plugins page in TypingMind.
Enable the Tableau MCP MCP tools.
Start a chat and choose the AI model you want to use.
Use the MCP tools in chat or assign them to an AI agent.
Switch to another AI model whenever needed without reconnecting MCP.

TypingMind chat using enabled MCP tools with a selected AI model

Frequently asked questions

What is the Tableau MCP MCP server used for?

Tableau MCP is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use Tableau MCP MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use Tableau MCP with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use Tableau MCP MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With Tableau MCP connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect Tableau MCP MCP to TypingMind?

Tableau MCP runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does Tableau MCP MCP provide in TypingMind?

Tableau MCP exposes 16 MCP tools that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use Tableau MCP MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If Tableau MCP requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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Tableau MCP

Overview

Official Documentation

Quick Start

Requirements

Deploy to Heroku

Example Prompts to Client

Prompt #1: Querying Data

Response

Prompt #2: Content Exploration

Response

Prompt #3: Getting a View

Response

Installation

Available Tools

Use Tableau MCP MCP with multiple AI models

Setup guide to use the local connector

Open the MCP settings

Run the connector command

Add Tableau MCP as a server

Use it across models

Frequently asked questions

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