Tableau MCP | OAuth 2.0 Tableau connector for AI agents

Tools your bi agent reaches for on Tableau, scoped per user.

CALL ANY TOOL

List workbooks and dashboards, download view data as CSV, browse published data sources, and monitor refresh jobs.

tableau_list_views

List views

List views (individual sheets and dashboards) within a specific workbook, or all views across an entire Tableau site. Supports filtering by name or owner and pagination.

Parameters

Name

Type

Required

Description

workbook_id

string

Required

The LUID of the workbook to list views from. If omitted, lists all views on the site.

filter

string

Optional

Filter expression using Tableau REST API filter syntax (e.g., name:eq:Sales Dashboard)

include_usage_statistics

boolean

Optional

Include view usage statistics (total views count) in the response

page_number

integer

Optional

Page number to retrieve (1-based)

page_size

integer

Optional

Number of views to return per page (max 1000)

tableau_job_get

Job get

tableau_jobs_list

Jobs list

tableau_site_get

Site get

tableau_job_cancel

Job cancel

tableau_user_get

User get

tableau_query_view

Query view

tableau_view_get

View get

tableau_sites_list

Sites list

tableau_session_get

Session get

tableau_users_list

Users list

tableau_user_update

User update

tableau_views_list

Views list

tableau_auth_signout

Auth signout

tableau_groups_list

Groups list

tableau_group_create

Group create

tableau_workbook_get

Workbook get

tableau_projects_list

Projects list

tableau_datasource_get

Datasource get

tableau_project_create

Project create

tableau_project_delete

Project delete

tableau_project_update

Project update

tableau_schedules_list

Schedules list

tableau_schedule_create

Schedule create

tableau_workbooks_list

Workbooks list

tableau_schedule_delete

Schedule delete

tableau_schedule_update

Schedule update

tableau_workbook_delete

Workbook delete

tableau_workbook_search

Workbook search

tableau_workbook_update

Workbook update

Build your Agent

Drop the toolkit in, point it at the user, and your bi agent can use Tableau from the first run.

import { ScalekitClient } from "@scalekit-sdk/node";
import { DynamicStructuredTool } from "@langchain/core/tools";
import { createReactAgent } from "@langchain/langgraph/prebuilt";
import { z } from "zod";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["tableau"], toolNames: ["tableau_workbooks_list", "tableau_views_list", "tableau_view_data"] },
  pageSize: 100,
});

const lcTools = tools.map((t) => new DynamicStructuredTool({
  name: t.tool.definition.name,
  description: t.tool.definition.description,
  schema: z.object({}).passthrough(),
  func: async (args) => {
    const { data } = await sk.tools.executeTool({
      toolName: t.tool.definition.name,
      identifier: "user_123",
      params: args,
    });
    return JSON.stringify(data);
  },
}));

const agent = createReactAgent({ llm, tools: lcTools });

import { ScalekitClient } from "@scalekit-sdk/node";
import OpenAI from "openai";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);
const openai = new OpenAI();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["tableau"], toolNames: ["tableau_workbooks_list", "tableau_views_list", "tableau_view_data"] },
  pageSize: 100,
});

const llmTools = tools.map((t) => ({
  type: "function",
  function: {
    name: t.tool.definition.name,
    description: t.tool.definition.description,
    parameters: t.tool.definition.input_schema,
  },
}));

const resp = await openai.responses.create({
  model: "gpt-4o", input: prompt, tools: llmTools,
});

import { ScalekitClient } from "@scalekit-sdk/node";
import Anthropic from "@anthropic-ai/sdk";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);
const anthropic = new Anthropic();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["tableau"], toolNames: ["tableau_workbooks_list", "tableau_views_list", "tableau_view_data"] },
  pageSize: 100,
});

const llmTools = tools.map((t) => ({
  name: t.tool.definition.name,
  description: t.tool.definition.description,
  input_schema: t.tool.definition.input_schema,
}));

const msg = await anthropic.messages.create({
  model: "claude-sonnet-4-6", max_tokens: 1024,
  tools: llmTools,
  messages: [{ role: "user", content: prompt }],
});

import { Agent } from "@google/adk/agents";
import {
  MCPToolset, StreamableHTTPConnectionParams,
} from "@google/adk/tools/mcp";

const toolset = new MCPToolset({
  connectionParams: new StreamableHTTPConnectionParams({
    url: "https://mcp.scalekit.com/tableau",
    headers: { Authorization: `Bearer ${userScopedToken}` },
  }),
});

const agent = new Agent({
  name: "agent", model: "gemini-2.0-flash",
  tools: await toolset.getTools(),
});

Try these prompts

Paste any prompt into your agent to start using Tableau.

Workbooks & views

Copy the prompt

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List all workbooks I have access to.

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List views in [workbook name].

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Pull data from [dashboard name].

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Which workbooks were updated this week?

Data & refreshes

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List all published data sources.

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Which extract refreshes failed today?

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Get data behind [view name] as CSV.

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Which refresh jobs are running right now?

Reporting

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Pull executive revenue dashboard data for Q3.

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Which dashboards have the most views this month?

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Get data from [sheet] in [workbook].

Copy the prompt

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List all workbooks with failed refreshes.

SEE HOW AUTH WORKS

Users authorize Tableau once. Their credentials stay vaulted, every call is checked, and every action is logged.

Authorize

Your user connects

Tableau

once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access

Who:

user ‘A’

when:

Once per user

access:

Limited to user

Store

Their

Tableau

token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection

vault:

encrypted

scope:

per-user

tokens:

auto-refreshed

Resolve

When your agent calls a

Tableau

tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs

speed:

~40ms

check:

before every call

seen by:

nobody

Audit

Every

Tableau

tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it

history:

90 days

export:

SIEM-ready

logged:

every call

Test other agents

Same per-user auth pattern across other bi agents and MCP connectors. Working code, live demos, fork what fits.

GTM and RevOps Teams

Revenue forecast commentary

Pulls open pipeline from Salesforce and HubSpot, calculates coverage against quota, flags at-risk stages, posts commentary to Slack, and logs every snapshot to Google Sheets.

GTM and RevOps Teams

Deal intelligence agent

Pulls recent Gong calls, scores deal risk with an LLM, cross-references the record in Attio, and DMs each owner their at-risk deals in Slack. Every read is scoped to that rep's own access.

Engineering Teams

Engineering standup agent

Pulls commits from GitHub and GitLab, tracks issue movement in Jira, and posts a per-engineer standup brief to Slack. Each engineer's activity is read on their own delegated OAuth.

GTM and RevOps Teams

Competitive intelligence briefing agent

Scans Gong calls for competitor mentions, matches each one to its Notion battlecard, and DMs every affected rep a single Slack digest per cycle. Every call runs as the PMM who owns the briefing, never a shared bot.

Why Scalekit

Secure your agent's access. Connectors ship in minutes

01.

Shared tokens break per-user analytics

A shared token looks fine in a demo. In production every call looks like a service account. Scalekit resolves the real user credential so attribution, audit, and scope stay accurate.

// shared token
 audit → bot_service_account
 user_filter → broken

 // scalekit
 audit → user_abc
 scope → enforced ✓

02.

Authentication is not authorization

03.

Multi-tenancy is architectural

04.

Tableau today. Others tomorrow.

“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”

Venu Madhav Kattagoni

Head of Engineering / Von

FAQs

Frequently Asked Questions

Does the agent access Tableau as the user or as a shared key?

As the user. Each workspace member authorizes once and Scalekit resolves their credential at request time. Audit logs attribute every action to that user, not a shared service account.

Where is the Tableau oauth 2.0 stored?

In Scalekit's managed AES-256 token vault, namespaced per tenant. Refresh is automatic. Revocation is a single dashboard action. Tokens never appear in prompts, logs, or LLM context.

Can I limit what the agent is allowed to do in Tableau?

Yes. Pass a tool name filter to listScopedTools so the BI agent only sees the subset you authorize. Pre-API-call scope checks block out-of-policy actions before the request reaches Tableau.

What happens when a user revokes Tableau access?

The connection is invalidated on the next tool call. Subsequent requests for that user fail closed with a clear error. Other users in the tenant remain unaffected. The event is logged for audit.

Can the agent access workbooks published by other users with restricted permissions?

Only workbooks the authorizing user has view access to in Tableau Server/Cloud. Row-level security rules on embedded data sources apply. Restricted workbooks are blocked at the Tableau permission layer.

On this page

Tool and actions Framework Compatibility Starter Prompt Auth Lifecycle Try Other Agents Why Scalekit