tableau-embed
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@tableau-embedShow me the Superstore Performance dashboard"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Tableau MCP App
Render a live, interactive Tableau dashboard inside ChatGPT, click a mark, and ask about what you clicked.
Not a screenshot and not a link out. The real viz, embedded in the conversation, filterable and hoverable — and when you select something, the selection is pushed to the model so that "why is this one so low?" resolves to the mark under your cursor.
You click Fasteners on the dashboard.
Fasteners selected on "KPI by Sub-Category" - nothing else is filtered.
Mark: Sub-Category: Fasteners | AGG(KPI Value): 8,532 | AGG(KPI Label): $8.5K
Parameters: Profit Bin Size = 200 | Top Customers = 5 | p.KPI = Sales
You: "why is this one so low?"
ChatGPT: "Sales: $8,532, lowest of 17 sub-categories. Average line sale: $37.26...
980 units across 226 orders. Average discount 7.9%, so discounting is
not the main cause. Profit: $2,429, a healthy 28.5% margin."Those numbers are queried live from the Tableau data source, not invented — verified against the raw query response, which is a distinction worth insisting on.
What this actually is
An MCP Apps server. It exposes one tool that
returns a ui:// resource — an HTML view the host mounts in a sandboxed iframe — which loads the
Tableau Embedding API, renders your viz, and reports the on-screen state back to the model as the
user interacts with it.
It deliberately returns no data of its own. The embed supplies the scope; a Tableau data query tool supplies the numbers. See How it works for why that split is the right one.
Related MCP server: Tableau MCP Server
Status, honestly
ChatGPT | Works. Renders, interacts, and pushes state; a selected mark was verified to scope the answer against a live query. You have to name the connector when asking — see Invoking it. |
Claude Desktop | Renders nothing. It approves the |
Tableau Public | Works anonymously, no credentials needed. |
Tableau Cloud | Works, via a Direct Trust Connected App JWT signed server-side. |
This is a working prototype built to answer a question — can you have a real conversation with a dashboard you're looking at? — and the answer turned out to be yes, with caveats worth reading.
Invoking it
Name the connector:
"Use the tableau-embed connector to show me the Superstore Performance dashboard"
This is the documented invocation, not a workaround for a bug. Asked without naming it, "show me the dashboard" reliably loses to ChatGPT's own chart builder, which will happily construct a convincing dashboard out of sample data and present it as an answer. Three rewrites of the tool description failed to change that. Once the dashboard is on screen, ordinary questions work normally — you only need to name the connector for the initial render.
Quickstart
Requires Node 18+ and, for the Cloud path, a Tableau Connected App.
git clone https://github.com/nuggenlabs/tableau-chatgpt-embed.git
cd tableau-chatgpt-embed
npm install
npm test # proves the viz renders under the real sandbox CSP, headlesslynpm test is worth running before anything else. It reproduces the MCP Apps iframe sandbox and
its Content Security Policy locally, drives a real Tableau viz through it in headless Chrome, and
tells you which of the four layers fails if one does. It also drives a real mark selection and
asserts the selection reaches the host — so a broken state push fails the build rather than
surfacing as a confused answer three weeks later.
To run it against a dashboard and connect it to ChatGPT:
cp .env.example .env # fill in, or delete the four credential lines for Tableau Public
npm startThen expose it over HTTPS and register the /mcp URL as a connector. On Windows, run.ps1 does
the whole sequence — server, tunnel, health check, paste-ready URL:
powershell -ExecutionPolicy Bypass -File .\run.ps1Full walkthrough, including the credential traps: docs/SETUP.md.
Documentation
Document | What's in it |
Credentials, tunnels, the startup preflight, and getting it into ChatGPT | |
Architecture, how on-screen state reaches the model, mark selection | |
What works where, and the Claude Desktop | |
Failures that cost real time here, and what each one actually was | |
A protocol for testing whether the model uses on-screen state |
Two findings worth stealing
A tool description is a routing instruction — and it can lose. "Show me the Superstore dashboard" was answered by ChatGPT building a plausible lookalike from a sample dataset — invented numbers, presented as an answer. Three successive rewrites of the description failed to win the request back, including one that names the competing behaviour and refuses the substitution outright. A tool competes with everything the host can do, not just its siblings in the same server, and against a first-party tool a description may simply not be enough. Unresolved — name the connector, as below.
Ask the harness, not the model. A model is not a reliable instrument for measuring its own
context. When on-screen state stopped reaching ChatGPT, four plausible theories each blamed the
wrong layer; what settled it was planting a random token in every push and asking for it back —
thirteen pushes, every call resolved, none delivered. docs/SCOPING-TEST.md is the general form of
that lesson.
Layout
src/
server.js MCP server: the tool, the ui:// resource, HTTP + stdio transports
view.html the embedded view - renders the viz, reads state, pushes it to the model
build-view.js inlines the MCP Apps client SDK into the view at build time
connected-app.js Direct Trust JWT minting for authenticated Cloud embeds
preflight.js startup credential and URL checks, so failures surface here not in ChatGPT
env.js dependency-light .env loader; shell variables win over the file
test/
sandbox-harness.js reproduces the host: the iframe sandbox, the CSP, the ui/ JSON-RPC contract
feasibility.test.js end-to-end - viz renders, host contract satisfied, state reaches the model
server.smoke.js MCP protocol correctness
preflight.test.js credential-failure classification, stubbed
env.test.js .env parsing and precedence
docs/ see the table above
run.ps1 Windows launcher: server + tunnel + health + paste-ready URLNo build step and three runtime dependencies. The Tableau Embedding API is loaded by the view at runtime from Tableau's own CDN, which the sandbox CSP has to allow — that constraint drives more of the design than anything else.
Not yet built
Choosing a dashboard by name. One viz is baked in at startup via
TABLEAU_VIZ_URL. Switching conflicts with the one-embed-per-conversation rule, which exists because a second embed mounts a fresh unfiltered viz and silently resets the reported scope.Inbound authentication.
/mcpis open to anyone who can reach it, andresources/readmints an embed token on demand. Fine behind an ephemeral tunnel; do not put this on a permanent public hostname without putting something in front of it.
License
MIT — see LICENSE.
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