---
title: MCP server
description: Connect MCP-aware assistants to Cube through a hosted HTTPS endpoint with OAuth and admin-managed defaults.
---

Cube MCP (Model Context Protocol) lets MCP-compatible AI clients connect to Cube over HTTPS using OAuth.

This page covers the **Cube connector**, which gives an AI assistant direct access to Cube
through MCP. It is not [Cube agent skills](/docs/integrations/agent-skills), which run in a
coding agent and operate Cube through the CLI, or
[Agent Skills in Cube](/docs/explore-analyze/skills), which are saved workflows your data
team authors for Analytics Chat.

<Note>

The MCP server is available on [Premium and Enterprise plans](https://cube.dev/pricing). <br />Users need the [Viewer][ref-roles] role or higher to interact with the MCP server. Which tools a
user sees depends on their role — see [Available actions](#available-actions).

</Note>


## What is MCP?

Model Context Protocol (MCP) is an open standard that enables AI assistants to securely connect to external data sources and tools. The Cube MCP server acts as a bridge between your AI assistant and Cube's analytics platform, allowing you to ask data questions directly from your coding environment.

## Overview

Cube hosts an MCP server endpoint. MCP clients connect over HTTPS and authenticate via OAuth.

- **Endpoint:** `https://cubecloud.dev/mcp`
- **OAuth flow:** Authorization Code + PKCE, `client_id` = `cube-mcp-client`, scope = `mcp-agent-access`. Clients discover it automatically from the endpoint — there is nothing to configure by hand.
- **Account selection:** You sign in to Cube as part of the OAuth flow and, if you belong to more than one account, choose which one to connect.
- **Deployment selection:** On connect, the client lands on the tenant **default deployment** set by your admin (or the first deployment you can access). Clients can also target a specific deployment and agent per request — see [Select a deployment and agent](#select-a-deployment-and-agent).

### One endpoint for everyone

`https://cubecloud.dev/mcp` is the same URL for every account, deployment and region. Cube
identifies your account from the OAuth token and routes each request to whichever
deployment serves it, so there is no per-tenant host to look up before you can connect.

<Note>

If Cube runs in your own cloud account or on your own domain, use that console domain
instead — `https://<your-console-domain>/mcp`.

</Note>

Each deployment also keeps a **region-specific endpoint**, shown under
**Admin → MCP Server**. Both work. Prefer the single endpoint above unless you need a
client to reach a deployment's region directly without passing through the control plane.

## Admin setup

### Prerequisites

Before enabling MCP, make sure you have:

- **Admin privileges** in your Cube instance
- An active Cube tenant

### 1) Check the MCP page

Go to **Admin → MCP Server**. The page shows the endpoint to hand to clients along with
ready-made setup snippets for each supported client. If it reads “MCP configuration is
unavailable,” the MCP server host isn’t configured for the account yet.

### 2) Configure deployment access

Go to **Admin → MCP Server** and use the **Deployment Access** section to control which
deployments MCP clients can reach and where they connect by default:

- **Default deployment** — the deployment MCP clients connect to unless they explicitly
  request another one. Choose **Automatic (first available)** to land each user on the
  first deployment they can access.
- **Limit available deployments** — when off (the default), MCP clients can access **all**
  deployments the user is permitted to see. Turn it on to restrict MCP to a chosen subset.
- **Available deployments** — when the limit is on, pick the deployments MCP clients may
  access. Selecting none disables MCP access for the account.

<Note>

Deployment access is always intersected with the user's
[role-based permissions][ref-roles] — clients can only reach deployments the
authenticated user is allowed to see.

</Note>

<Frame>
  <img src="/images/docs/integrations/mcp-deployment-access.png" alt="Admin MCP Server page showing the Deployment Access section with the default deployment dropdown, the Limit available deployments switch, and the available deployments picker" />
</Frame>

## Connect to Claude

Cube is available in the
[Claude Connectors Directory](https://claude.ai/customize/connectors). Connect it once
and use it in Claude on the web, desktop, or Claude Code—there is no endpoint to paste or
local server to configure.

1. In Claude on the web or desktop, open **Customize → Connectors**.
2. Click **+**, choose **Browse connectors**, and search for **Cube**.
3. Select Cube and click **Connect**.
4. Complete the Cube OAuth flow and choose your tenant.

On a Team or Enterprise plan, an owner may need to enable Cube first under
**Admin Settings → Connectors**.

To use Cube in a chat, open the tools menu and enable the Cube connector, then ask a data
question. In Claude Code, run `/mcp` to confirm the connector is available and authenticate
if prompted.

<Frame>
  <img src="https://lgo0ecceic.ucarecd.net/68c3e7e2-def2-4aec-84a5-8cded3473def/" />
</Frame>

## Connect to Cursor

Add the MCP endpoint under Tools & MCP Settings, then complete the OAuth flow.

```json
{
  "mcpServers": {
    "cube-mcp-server": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "--transport", "http", "https://cubecloud.dev/mcp"]
    }
  }
}
```

## Connect to Codex

Preferred (CLI):

```bash
codex mcp add cube-mcp-server --url https://cubecloud.dev/mcp
```

If this is your first time using MCP in Codex, enable the feature in `~/.codex/config.toml`:

```editorconfig
[features]
rmcp_client = true
```

Manual setup:

```editorconfig
[features]
rmcp_client = true

[mcp_servers."cube-mcp-server"]
url = "https://cubecloud.dev/mcp"
```

Then run `codex mcp login cube-mcp-server` to authenticate.

## Connect to other MCP clients

For any MCP-compatible client:

1. Add a new server with the **MCP endpoint**.
2. The client will auto-discover OAuth and prompt for authentication.
3. Complete the OAuth flow to grant access to your Cube deployment.

## Select a deployment and agent

An MCP client is not locked to a single deployment for the whole session. After
connecting, it can discover the deployments and agents you can access and target a
specific one on each request.

Three tools work together:

- **`listDeployments`** — discovery. Returns every deployment you can access via MCP
  (already filtered by the admin's deployment-access settings and your permissions) and
  each deployment's agents. Use it to find valid `deploymentId` and `agentId` values
  before calling `chat`. Every deployment offers an **Auto** agent (`agentId: null`) in
  addition to any configured agents.
- **`chat`** — accepts two optional selection parameters:
  - **`deploymentId`** — the deployment to use for this request. When omitted, the chat
    uses the deployment from the current session (the default resolved at connect time).
  - **`agentId`** — the agent to use for this request. When omitted or `null`, the
    deployment's **Auto** agent is used. Pass a specific `agentId` to route to a
    configured agent.
- **`loadQueryResults`** — paginates through the results of a previous query on the same
  deployment context.

A typical client workflow:

<Steps>
  <Step title="Connect">
    Complete the OAuth flow. The session is scoped to the tenant default deployment (or
    the first one you can access).
  </Step>
  <Step title="Discover">
    Call `listDeployments` to see the available `deploymentId` / `agentId` values.
  </Step>
  <Step title="Chat">
    Call `chat` with your `input`, optionally passing `deploymentId` and/or `agentId` to
    target a specific deployment or agent. Omit both to use the session default deployment
    with its Auto agent.
  </Step>
</Steps>

Requests are always validated against the admin's deployment-access settings. A deployment
that is outside the allow-list — or that you don't have permission to see — is rejected
with a **403 Forbidden** (`Deployment <id> is not available via MCP for this account`), so
neither `listDeployments` nor the `chat` selection can reach an excluded deployment.

## Available actions

The MCP server exposes 23 tools, grouped below.

Every tool runs as the authenticated user. Queries respect the same
[permissions][ref-roles] as the rest of Cube, including row-level security — MCP is a new
way to reach your data, not a new access surface.

### Read and write tools

Each tool is annotated as read-only or destructive. MCP clients that honor these
annotations — including Claude — run read-only tools automatically and **always ask for
confirmation** before any of the six destructive ones: `updateReport`, `deleteReport`,
`updateDashboard`, `publishDashboard`, `writeDataModelFile`, and `deleteDataModelFile`.
Nothing that changes a workbook report, an exploration, a dashboard, or your data model
happens without an explicit approval.

### Deployments and chat

| Tool | Description |
| --- | --- |
| `listDeployments` | Lists the deployments and agents you can reach over MCP. |
| `chat` | Asks a question of a Cube agent, optionally targeting a specific deployment and agent. |
| `loadQueryResults` | Paginates through the results of a previous query. |

See [Select a deployment and agent](#select-a-deployment-and-agent) for how these three
work together.

### Query and discovery

| Tool | Description | Access |
| --- | --- | --- |
| `searchDataModel` | Searches the semantic model by similarity — views and their measures and dimensions — to discover what is queryable. Returns compact records (name, title, description, type) to reference in `runQuery`. | Read-only |
| `runQuery` | Runs a Cube SQL query (PostgreSQL dialect) against the [SQL API][ref-sql-api]. Returns a schema, a page of rows, and `hasMore` / `totalRows` for pagination via `offset`. Pass the dev `branchName` from `startDataModelEdit` to query that branch instead of the deployed model. | Read-only |

Call `searchDataModel` before `runQuery` to find exact view and member names rather than
guessing them.

Omitting `branchName` queries the deployed model, exactly as before this parameter existed.
Passing a `branchName` that isn't an active dev branch — for example the deploy branch's own
name, or a feature branch with no dev worker running — fails with an error rather than
silently answering from the deployed model, so a query aimed at the wrong branch never
looks like a query that just returned no rows.

### Dashboard authoring

These tools build [workbooks][ref-workbooks] and [dashboards][ref-dashboards]
programmatically. Creating and editing workbooks requires the Explorer role or higher.

| Tool | Description | Access |
| --- | --- | --- |
| `readWorkbook` | Reads a workbook — its name and its current dashboard draft and published configs. | Read-only |
| `createWorkbook` | Creates a new empty workbook, the container that holds reports and a dashboard. | Write |
| `createReport` | Saves a query plus its visualization. Pass `workbookId` to create a report inside a workbook and get the `reportId` a chart widget references; omit `workbookId` to save a standalone [exploration](/docs/explore-analyze/explore#saving-explorations) instead. | Write |
| `readReport` | Reads one workbook report or standalone exploration by id — its title, SQL, chart spec, placement, and a shareable URL. | Read-only |
| `updateReport` | Edits an existing workbook report or exploration in place, keeping its `reportId`. Send only the fields you want to change. | Destructive — prompts |
| `deleteReport` | Deletes a workbook report or exploration. | Destructive — prompts |
| `updateDashboard` | Saves the dashboard layout to the workbook **draft**. Replaces the full widget set and does not go live. | Destructive — prompts |
| `publishDashboard` | Publishes the current draft to make it live. Idempotent — republishing an unchanged draft is a no-op. | Destructive — prompts |

Drafts are the safety net here: `updateDashboard` only ever writes to the draft, so a
published dashboard keeps serving its previous version until you approve
`publishDashboard`. See [Build a dashboard](#build-a-dashboard) for the full sequence.

**To change an existing report, use `updateReport` — never recreate it.** A dashboard's
chart widget points at a specific `reportId`, so replacing a report with a new one orphans
every widget referencing it. The same caution applies to moving a report between workbooks:
a widget resolves its report from its *own* workbook's report list, so changing a report's
`workbookId` empties the tiles on the old workbook's dashboard. Call `readWorkbook` and
re-point those widgets with `updateDashboard` first.

### Data model editing

These tools read and edit the semantic model **source** files. They are registered only
for users whose role grants permission to edit the semantic model — Admin and Developer by
default. Users without it never see them.

| Tool | Description | Access |
| --- | --- | --- |
| `listDataModelFiles` | Lists the semantic model source files (raw YAML, JavaScript, or Python). | Read-only |
| `readDataModelFile` | Reads one file's raw source. | Read-only |
| `startDataModelEdit` | Enters [development mode][ref-dev-mode], starts a dev worker, and returns the dev `branchName` that every write tool requires. | Write |
| `writeDataModelFile` | Creates or overwrites a model source file on the dev branch (whole-file replacement). Recompiles the model and reports `valid` plus any `validationError`. | Destructive — prompts |
| `deleteDataModelFile` | Deletes a model source file on the dev branch. | Destructive — prompts |
| `getDataModelChanges` | Shows the diff of the dev branch against its parent — the pending changes, for review before committing. | Read-only |
| `getBranchDiff` | Shows what **any** branch changed against the deploy branch: the changed-file list with per-file line counts, plus the unified diff. | Read-only |
| `getDeploymentEnv` | Lists the deployment's environment variables, with every secret-looking value redacted to `[ENCRYPTED]`. Useful for confirming configuration is present and shaped as expected. | Read-only |

`getDataModelChanges` answers "what have I changed?" for your own dev branch against its
immediate parent. `getBranchDiff` answers "what did this branch change?" for any branch,
including feature branches — reach for it when a change edits existing cubes, where the
file list looks identical on both branches and `listDataModelFiles` reveals nothing.

<Note>

`getDeploymentEnv` never returns secret values. Anything that looks like a credential is
replaced with `[ENCRYPTED]` before it leaves Cube, so an AI client can verify that a
variable is set without ever seeing what it is set to.

</Note>

#### How model edits stay safe

Letting an AI client edit your semantic model is safe because of four constraints built
into the MCP server:

- **Edits never touch production.** Every write goes to a personal dev branch named
  `dev-<user>-<hash>`. The write tools reject any branch that isn't a dev branch, so
  the deploy branch is never writable over MCP.
- **`startDataModelEdit` is the only entry point.** It returns the dev `branchName`, and
  `writeDataModelFile` and `deleteDataModelFile` require it. There is no way to write
  without going through it first.
- **Promotion is manual and human.** To publish model changes you commit the dev branch
  from the Cube UI, as described in [Development mode][ref-dev-mode]. The MCP server
  deliberately exposes no commit tool — an AI client can prepare changes, but only a
  person can ship them.
- **Registration is permission-gated.** Every tool in the two sections above — the six
  model-editing tools, `getBranchDiff`, `getDeploymentEnv`, and both pre-aggregation
  tools — is offered only to users whose role allows editing the semantic model. A Viewer
  never sees them at all.
- **Verification happens on the branch, before a merge, not after.** Pass the dev
  `branchName` to `runQuery` to check that an edit returns the right data — `valid: true`
  from `writeDataModelFile` only means the model compiles, not that it's correct.

Review pending work with `getDataModelChanges` before you commit.

### Pre-aggregations

These tools inspect and trigger [pre-aggregation][ref-pre-aggregations] builds. They are
registered under the same semantic-model permission as the data model tools above.

| Tool | Description | Access |
| --- | --- | --- |
| `getPreAggregationStatus` | Lists the data model's pre-aggregations with their definitions and, for each, how many partitions exist, how many were built, when the newest build landed, and the exact error if a build failed. | Read-only |
| `buildPreAggregation` | Queues an on-demand build of one pre-aggregation and returns once it is accepted. The build runs asynchronously. | Write |

Together these close the loop on pre-aggregation work: a query alone cannot prove a rollup
was used, and external pre-aggregations fail in configuration-specific ways — a missing
export bucket, denied bucket permissions — that only an actual build surfaces. Call
`buildPreAggregation`, then poll `getPreAggregationStatus` to see whether the partitions
built or to read the failure.

<Note>

`buildPreAggregation` runs real queries against your data warehouse and, for external
pre-aggregations, writes through the export bucket. It consumes warehouse resources, so
expect a cost per build.

</Note>

## Example workflows

### Ask a data question

Ask a question in natural language and let the agent do the planning: `chat` returns the
answer along with the SQL it generated, and `loadQueryResults` pages through large result
sets. Use this for summaries, trends, and ad-hoc analysis.

To drive the query yourself instead, call `searchDataModel` to find the right view and
members, then run your own SQL with `runQuery`.

<Frame>
  <img src="https://lgo0ecceic.ucarecd.net/102c3c3e-3657-42aa-8d3d-2029ca21115c/" />
</Frame>

### Build a dashboard

Four of the dashboard tools build a new dashboard, and they are designed to be used in
order. The rest — `readWorkbook`, `readReport`, `updateReport`, `deleteReport` — are for
inspecting and changing one that already exists.

<Steps>
  <Step title="Create the workbook">
    Call `createWorkbook` with a name. It returns the `workbookId` every later step needs.
    If you were given an existing workbook to build into, call `readWorkbook` instead and
    skip to the next step.
  </Step>
  <Step title="Create a report per chart">
    Call `createReport` once per chart, KPI tile, or table, passing the `workbookId` and
    the SQL query that powers it. Each call returns a `reportId`.
  </Step>
  <Step title="Lay out the dashboard">
    Call `updateDashboard` with the complete widget set, referencing each `reportId` from
    the previous step. This replaces the draft layout and saves to the workbook draft —
    the live dashboard is unchanged. Your client will ask you to confirm.
  </Step>
  <Step title="Publish">
    Review the draft, then call `publishDashboard` to make it live. This also prompts for
    confirmation. It returns the dashboard URL.
  </Step>
</Steps>

To change a dashboard later, call `readWorkbook` first and edit on top of the current
draft rather than overwriting it. To change one chart rather than the layout, call
`readReport` on the widget's `reportId` and edit it with `updateReport` — that keeps the
id, so every widget pointing at it keeps rendering.

### Edit the data model

Call `startDataModelEdit` to enter development mode and get a dev `branchName`. Explore
the current source with `listDataModelFiles` and `readDataModelFile`, then apply changes
with `writeDataModelFile` or `deleteDataModelFile`, passing that `branchName`. Each write
recompiles the model and reports validation errors, so you can iterate until it compiles.
Before committing, verify the change returns the right data: call `runQuery` with the same
`branchName` and check the numbers, since a compiling model can still return wrong results.
Review the result with `getDataModelChanges`, then commit the branch from the Cube UI to
publish it.

To review a branch you didn't author — a colleague's feature branch, say — call
`getBranchDiff` with its name instead. It compares against the deploy branch and returns
the full changed-file list even when the patch itself is trimmed.

### Verify a pre-aggregation

After adding or changing a pre-aggregation, call `getPreAggregationStatus` to see whether
its partitions exist and when they were last built. If nothing has been built yet — or you
want to confirm an external pre-aggregation's export bucket actually works — call
`buildPreAggregation`, then poll `getPreAggregationStatus` again. A failed build reports
the exact error, which is usually a configuration problem rather than a modeling one;
`getDeploymentEnv` will tell you whether the expected variables (`CUBEJS_DB_EXPORT_BUCKET`
and friends) are set.

## Troubleshooting

- **MCP configuration is unavailable**: Configure the MCP server URL.
- **MCP OAuth integration is not configured**: Enable MCP in **Admin → Team & Security → OAuth Integrations**.
- **No deployments available / MCP access is disabled**: In **Admin → MCP Server → Deployment Access**, make sure **Limit available deployments** is off, or that at least one deployment is selected and the user has permission to access it.
- **`Deployment <id> is not available via MCP for this account` (403)**: The requested deployment is excluded by the deployment-access allow-list or by the user's permissions. Call `listDeployments` to see which deployments are reachable, or adjust the allow-list in **Admin → MCP Server → Deployment Access**.

[ref-roles]: /admin/users-and-permissions/roles-and-permissions
[ref-pre-aggregations]: /docs/pre-aggregations/using-pre-aggregations
[ref-sql-api]: /reference/core-data-apis/sql-api
[ref-workbooks]: /docs/explore-analyze/workbooks
[ref-dashboards]: /docs/explore-analyze/dashboards
[ref-dev-mode]: /docs/data-modeling/dev-mode
