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Using AI with Superset

Superset supports AI assistants through the Model Context Protocol (MCP). Connect Claude, ChatGPT, or other MCP-compatible clients to explore your data, build charts, create dashboards, and run SQL -- all through natural language.

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Requires Superset 5.0+. Your admin must enable and deploy the MCP server before you can connect. See the MCP Server admin guide for setup instructions.

What Can AI Do with Superset?

Explore Your Data

Ask your AI assistant to browse what's available in your Superset instance:

List datasets -- see all datasets you have access to, with filtering and search
Get dataset details -- column names, types, available metrics, and filters
List charts and dashboards -- find existing visualizations by name or keyword
Get chart and dashboard details -- understand what a chart shows, its query, and configuration

Example prompts:

"What datasets are available?" "Show me the columns in the sales_orders dataset" "Find dashboards related to revenue"

Build Charts

Describe the visualization you want and AI creates it for you:

Preview-first workflow -- by default AI generates an Explore link so you can review the chart before it is saved. Say "save it" to commit permanently
Create charts from natural language -- describe what you want to see and AI picks the right chart type, metrics, and dimensions
Preview before saving -- generate_chart defaults to save_chart=False, showing the chart in Explore before it's committed. Ask AI to save once you're satisfied.
Modify existing charts -- update_chart also supports preview mode so you can review changes before saving (update filters, change chart types, add metrics)
Get Explore links -- open any chart in Superset's Explore view for further refinement

Example prompts:

"Create a bar chart showing monthly revenue by region from the sales dataset" "Update chart 42 to use a line chart instead" "Give me a link to explore this chart further"

Preview-first workflow

Charts are not saved by default. The workflow is intentionally iterative:

Explore — AI generates an Explore link so you can see the chart before it exists in Superset
Iterate — ask the AI to adjust the chart; changes are previewed without touching the database
Save — when you're happy, say "save it" and the chart is permanently stored

To skip the preview and save immediately, include "and save it" in your prompt.

Create Dashboards

Build dashboards from a collection of charts:

Generate dashboards -- create a new dashboard with a set of charts, automatically laid out
Add charts to existing dashboards -- place a chart on an existing dashboard with automatic positioning

Example prompts:

"Create a dashboard called 'Q4 Sales Overview' with charts 10, 15, and 22" "Add the revenue trend chart to the executive dashboard"

Browse Databases

Discover what database connections are configured in your Superset instance:

List databases -- see all database connections you have access to
Get database details -- name, backend type (PostgreSQL, Snowflake, etc.), and connection status

Example prompts:

"What databases are connected to Superset?" "Show me details about the data warehouse connection"

Create Virtual Datasets

Build ad-hoc SQL datasets that can be used as the basis for charts:

Create virtual datasets -- write a SQL query and save it as a reusable dataset
Use immediately in charts -- the returned dataset ID can be passed directly to chart creation

Example prompts:

"Create a dataset from: SELECT region, SUM(revenue) as total_revenue FROM orders GROUP BY region" "Make a virtual dataset called 'monthly_signups' from the users table filtered to last 12 months"

Run SQL Queries

Execute SQL directly through your AI assistant:

Run queries -- execute SQL with full Superset RBAC enforcement (you can only query data your roles allow)
Open SQL Lab -- get a link to SQL Lab pre-populated with a query, ready to run and explore
Save queries -- save a SQL query to SQL Lab's Saved Queries for later reuse

Example prompts:

"Run this query: SELECT region, SUM(revenue) FROM sales GROUP BY region" "Open SQL Lab with a query to show the top 10 customers by order count" "Save this query as 'Weekly Revenue Report'"

Analyze Chart Data

Pull the raw data behind any chart:

Get chart data -- retrieve the data a chart displays, with support for JSON, CSV, and Excel export formats
Inspect results -- useful for verifying what a visualization shows or feeding data into other tools

Example prompts:

"Get the data behind chart 42" "Export chart 15 data as CSV"

Check Instance Status

Health check -- verify your Superset instance is up and the MCP connection is working
Instance info -- get high-level statistics about your Superset instance (number of datasets, charts, dashboards)

Example prompts:

"Is Superset healthy?" "How many dashboards are in this instance?"

Connecting Your AI Client

Once your admin has deployed the MCP server, connect your AI client using the instructions below.

Claude Desktop

Edit your Claude Desktop config file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
Linux: ~/.config/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "superset": {
      "url": "http://localhost:5008/mcp"
    }
  }
}

Restart Claude Desktop. The hammer icon in the chat bar confirms the connection.

If your admin has enabled JWT authentication, you may need to include a token:

{
  "mcpServers": {
    "superset": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote@latest",
        "http://your-superset-host:5008/mcp",
        "--header",
        "Authorization: Bearer YOUR_TOKEN"
      ]
    }
  }
}

Claude Code (CLI)

Add to your project's .mcp.json:

{
  "mcpServers": {
    "superset": {
      "type": "url",
      "url": "http://localhost:5008/mcp"
    }
  }
}

ChatGPT

Click your profile icon > Settings > Apps and Connectors
Enable Developer Mode in Advanced Settings
In the chat composer, press + > Add sources > App > Connect more > Create app
Enter a name and your MCP server URL
Click I understand and continue

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ChatGPT MCP connectors require a Pro, Team, Enterprise, or Edu plan.

Ask your admin for the MCP server URL and any authentication tokens you need.

Tips for Best Results

Be specific -- "Create a bar chart of monthly revenue by region from the sales dataset" works better than "Make me a chart"
Start with exploration -- ask what datasets and charts exist before creating new ones
Review AI-generated content -- always check chart configurations and SQL before saving or sharing
Use Explore for refinement -- ask AI for an Explore link, then fine-tune interactively in the Superset UI
Check permissions if you get errors -- AI respects Superset's RBAC, so you can only access data your roles allow

Available Tools Reference

Exploration & Discovery

Tool	Description
`health_check`	Verify the MCP server is running and connected
`get_instance_info`	Get instance statistics (dataset, chart, dashboard counts)
`get_schema`	Discover available charts, datasets, and dashboards with schema info

Datasets

Tool	Description
`list_datasets`	List datasets with filtering and search
`get_dataset_info`	Get dataset metadata (columns, metrics, filters)
`create_virtual_dataset`	Create a virtual dataset from a SQL query

Charts

Tool	Description
`list_charts`	List charts with filtering and search
`get_chart_info`	Get chart metadata and configuration
`get_chart_data`	Retrieve chart data (JSON, CSV, or Excel)
`get_chart_preview`	Generate a chart preview (URL, ASCII, table, or Vega-Lite)
`get_chart_type_schema`	Get the configuration schema for a chart type
`generate_chart`	Create a new chart from a specification (defaults to preview mode — review before saving)
`update_chart`	Modify an existing chart's configuration (pass `generate_preview=False` to persist immediately instead of returning a preview URL)
`update_chart_preview`	Update a cached chart preview without saving
`generate_explore_link`	Generate an Explore URL for interactive visualization

Dashboards

Tool	Description
`list_dashboards`	List dashboards with filtering and search
`get_dashboard_info`	Get dashboard metadata and layout
`generate_dashboard`	Create a new dashboard with specified charts
`add_chart_to_existing_dashboard`	Add a chart to an existing dashboard

SQL

Tool	Description
`execute_sql`	Run a SQL query with RBAC enforcement
`save_sql_query`	Persist a SQL query to SQL Lab's saved queries
`open_sql_lab_with_context`	Open SQL Lab with a pre-populated query

Databases

Tool	Description
`list_databases`	List configured database connections
`get_database_info`	Get details about a specific database connection

Troubleshooting

"Connection refused" or "Cannot connect"

Confirm the MCP server URL with your admin
For Claude Desktop: fully quit the app (not just close the window) and restart after config changes
Check that the URL path ends with /mcp (e.g., http://localhost:5008/mcp)

"Permission denied" or missing data

Superset's RBAC controls what you can access through AI, just like in the Superset UI
Ask your admin to verify your roles and permissions
Try accessing the same data through the Superset web UI to confirm your access

"Response too large"

Ask for smaller result sets: use filters, reduce page_size, or request specific columns
Example: "Show me the top 10 rows from the sales dataset" instead of "Show me all sales data"

AI doesn't see Superset tools

Verify the connection in your AI client (e.g., the hammer icon in Claude Desktop)
Ask the AI "What Superset tools are available?" to confirm the connection
Restart your AI client if you recently changed the configuration

What Can AI Do with Superset?​

Explore Your Data​

Build Charts​

Create Dashboards​

Browse Databases​

Create Virtual Datasets​

Run SQL Queries​

Analyze Chart Data​

Check Instance Status​

Connecting Your AI Client​

Claude Desktop​

Claude Code (CLI)​

ChatGPT​

Tips for Best Results​

Available Tools Reference​

Exploration & Discovery​

Datasets​

Charts​

Dashboards​

SQL​

Databases​

Troubleshooting​

"Connection refused" or "Cannot connect"​

"Permission denied" or missing data​

"Response too large"​

AI doesn't see Superset tools​

What Can AI Do with Superset?

Explore Your Data

Build Charts

Create Dashboards

Browse Databases

Create Virtual Datasets

Run SQL Queries

Analyze Chart Data

Check Instance Status

Connecting Your AI Client

Claude Desktop

Claude Code (CLI)

ChatGPT

Tips for Best Results

Available Tools Reference

Exploration & Discovery

Datasets

Charts

Dashboards

SQL

Databases

Troubleshooting

"Connection refused" or "Cannot connect"

"Permission denied" or missing data

"Response too large"

AI doesn't see Superset tools