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  1. Home
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  3. MCP Superset
MCP Superset logo
Health: ActiveRecent health check succeeded.Last checked 9/9/2026, 2:02:04 PM

MCP Superset

User RatingsBe the first to rate and review this MCP server!
View Repository56 GitHub StarsTotal stargazers on GitHub for the source repository (56 stars).Visit Website
apache-supersetdata-platformsdashboardssqlaccess-control

Manage Superset dashboards, charts, datasets, SQL Lab, security, and access controls through MCP.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent โ€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag โ€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON โ–พ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "bintocher-mcp-superset": {
      "command": "uvx",
      "args": [
        "support"
      ]
    }
  }
}

๐Ÿ’ก Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Tool Schemas (80) Directory Badge Claim listing Alternatives๐Ÿ“Š More in Data Platforms

Overview

The bintocher/mcp-superset MCP server exposes Apache Superset administration and analytics operations through 137 MCP tools. It supports dashboard and chart CRUD, datasets, SQL Lab, users, roles, row-level security, groups, permissions audits, reports, tags, and asset import/export. Run it locally with stdio or serve it over streamable HTTP or SSE, using JWT authentication or a Superset session cookie. Reach for it when an AI client needs to inspect, modify, or govern Superset resources with confirmation checks and SQL safety controls.

Use cases

โ€ขManage Superset dashboards and native filters
โ€ขQuery saved charts and SQL Lab data
โ€ขAudit user, dataset, and dashboard permissions
โ€ขAutomate Superset asset export and import

Key features

โ€ข137 MCP tools for Apache Superset
โ€ขDashboard and chart CRUD with import/export
โ€ขSQL Lab query execution and CSV export
โ€ขUser, role, group, and RLS management
โ€ขConfirmation checks and DDL/DML blocking
โ€ขHTTP, SSE, and stdio transports

Capabilities & Tool Schemas (80) ~1.1k tokensApproximate context cost of this serverโ€™s tool schemas (~4 chars/token), before any tool is called. Actual usage depends on your client and model.Self-reported Self-reportedParsed from the repository README, not verified against a live server โ€” may be incomplete or out of date.

Inspect callable tools, capabilities, and parameters exposed to AI agents by MCP Superset.

superset_dashboard_list

List dashboards with filtering and pagination

superset_dashboard_get

Get dashboard details by ID

superset_dashboard_create

Create a new dashboard

superset_dashboard_update

Update dashboard properties

superset_dashboard_delete

Delete a dashboard (requires confirmation)

superset_dashboard_copy

Duplicate a dashboard

How MCP Superset works

What bintocher/mcp-superset MCP server does

The bintocher/mcp-superset MCP server connects an MCP-compatible client to an Apache Superset instance. Its 137 tools cover administrative, content-management, analytics, and access-control workflows. Dashboard operations include listing, filtering, creating, updating, copying, publishing, exporting, importing, and managing native filters or embedded settings. Chart tools support CRUD operations, duplication, saved-chart data retrieval, query execution, and asset transfer.

Beyond dashboards and charts, the project covers databases, datasets, SQL Lab, users, roles, permissions, row-level security, groups, reports, annotations, tags, and saved queries. It also provides access-control operations for dashboards and automatic datasource permission synchronization, plus a permissions matrix for auditing access across users, dashboards, datasets, and RLS rules.

How it works

The server communicates with Superset through its REST API and presents those operations as MCP tools. It can run with streamable HTTP, SSE, or stdio transport. HTTP is the default transport, while stdio is suitable for desktop clients that launch the process locally. The bind host, port, and transport can be selected with command-line options or environment variables.

Authentication can use Superset username and password credentials, with the authentication provider set to database or LDAP. For Superset deployments behind SSO, OAuth, or SAML, the server can instead send a browser session cookie. Cookie authentication does not renew the session; an expired cookie requires a new value and a server restart. JWT handling includes token refresh and CSRF handling when using the credential-based login flow.

Setup and configuration

Install the mcp-superset package from PyPI with pip, uv, or uvx. Running uvx mcp-superset starts the server without a separate installation. A local .env file or exported variables should define SUPERSET_BASE_URL, SUPERSET_USERNAME, and SUPERSET_PASSWORD for the standard login path. SUPERSET_AUTH_PROVIDER selects db or ldap.

For session-cookie authentication, set SUPERSET_SESSION_COOKIE and, when necessary, SUPERSET_SESSION_COOKIE_NAME. The cookie name defaults to session, but Superset deployments may configure another name. SUPERSET_MCP_HOST, SUPERSET_MCP_PORT, and SUPERSET_MCP_TRANSPORT control server binding and transport. The CLI also accepts --env-file for a specific environment file.

The bintocher/mcp-superset MCP server can be added to Claude Desktop with a stdio command such as uvx mcp-superset --transport stdio. The README also documents HTTP configuration for Claude Code and identifies Cursor as a stdio use case.

Tools and capabilities

  • Manage dashboards, charts, datasets, databases, tags, reports, annotations, and saved queries.
  • Execute SQL Lab queries, format SQL, estimate query cost, and export results as CSV.
  • Inspect chart data and dashboard relationships, including the charts and datasets used by a dashboard.
  • Configure dashboard native filters and embedded-mode domains.
  • Manage users, roles, permissions, groups, and row-level security rules.
  • Export and import dashboards, charts, datasets, and complete instance assets.
  • Apply confirmation requirements to destructive actions and block DDL or DML in SQL Lab.

Limitations and notes

The bintocher/mcp-superset MCP server requires access to a compatible Superset deployment and credentials or a valid session cookie. The README targets Superset 6.0.1. Session cookies grant the associated Superset account's access for their lifetime, so they should be treated as credentials and kept out of shell history and committed configuration. Destructive operations such as deletion and filter resets require confirmation, and SQL Lab safety restrictions may prevent DDL or DML statements.

Read the full README โ†’View source on GitHub โ†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks โ€” not a rating.

GitHub stars
56
Stargazers on the source repository.
Last commit
10d ago
Most recent push to the default branch.
Tools exposed
80
Callable tools this server registers over MCP.
Directory activity
3 views
Config copies, upvotes, and views on AllMCPs.

Reviews

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Frequently Asked Questions about MCP Superset

Install it from PyPI with pip or uv, or run it without installation using `uvx mcp-superset`.

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Technical Specs & Signals

Category๐Ÿ“ŠData Platforms
PricingFree
More technical detailsExpand โ–พ
TransportSTDIO
RuntimePython
AuthOther
LicenseMIT
ClientsClaude Desktop, Cursor
Last updatedSep 7, 2026
10/10 checks healthy over the last 32d
Views3
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars56
GitHub Star CountTotal stargazers on GitHub representing community popularity (56 stars).
Last commit10d ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Sep 1, 2026
61Quality signal: Good ยท 61/100How this signal is calculated โ–พ
Server availabilityNot measured

Not scored for repo-hosted servers โ€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools29/30
Adoption & activity7/15
Community engagement0/10

A guidance signal from public completeness & health data โ€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 21d ago via OSV.dev ยท support (PyPI)

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