Chat with your data. Anywhere.
Databox MCP is a Model Context Protocol server that connects your business data to AI assistants. Ask questions about your metrics in plain English—no SQL, no dashboard building, no data exports.
Databox MCP enables AI tools like Claude, Cursor, n8n, and Gemini CLI to access and analyze your Databox data conversationally. It transforms how you interact with business metrics—instead of navigating dashboards, you simply ask questions and get instant answers.
Key Benefits:
- Query your data using natural language
- Works with 130+ existing Databox integrations
- No additional cost for Databox users
- Setup in under 60 seconds
| Client | Status |
|---|---|
| Claude Desktop | Supported |
| Claude Web | Supported |
| Cursor | Supported |
| n8n | Supported |
| Gemini CLI | Supported |
| Any MCP-compatible tool | Supported |
Add to your claude_desktop_config.json:
{
"mcpServers": {
"databox": {
"type": "http",
"url": "https://mcp.databox.com/mcp"
}
}
}- Go to Settings → Connectors
- Click Add Custom Connector
- Enter the remote server URL:
https://mcp.databox.com/mcp - Complete the authorization flow
Add the Databox MCP server in Cursor's MCP settings with the URL https://mcp.databox.com/mcp.
Use an HTTP Request node pointing to https://mcp.databox.com/mcp and build your workflows from there.
Databox MCP exposes 11 tools for interacting with your data:
- list_accounts – List all Databox accounts you have access to
- list_data_sources – List data sources for an account
- create_data_source – Create a new data source
- delete_data_source – Remove a data source
- list_data_source_datasets – List datasets within a data source
- create_dataset – Create a new dataset with schema definition
- delete_dataset – Remove a dataset
- ingest_data – Push data records into a dataset
- get_ingestion – Check ingestion status and metrics
- get_ingestions – List all ingestions for a dataset
- ask_genie – Query your data using natural language (powered by Genie AI)
- Supports conversation threading for follow-up questions
- Translates business questions into precise queries
- Returns calculated results, not LLM approximations
Databox MCP uses a three-layer architecture to ensure accurate, reliable answers:
- Data Platform – Structured datasets with schemas, types, and validation
- Analytic Query Engine – Executes actual queries (aggregations, joins, filters)
- Semantic Layer – Understands business definitions and metric relationships
The AI never touches your calculations directly. It formulates queries, the engine executes them, and the AI summarizes the results. This means you get real calculations, not statistical approximations.
Databox MCP uses secure authentication:
- OAuth 2.0 for user authorization
- JWT token validation for secure sessions
- API key authentication for programmatic access
Your data remains within your Databox account with existing governance standards. AI access is limited to explicitly granted data permissions.
- Encrypted connections (HTTPS)
- Scope-based authorization
- Audit trails and ingestion history
- No vendor lock-in (universal MCP standard)
- Data isolation per account
Ad-hoc Analysis
"What was our conversion rate last week compared to the previous week?"
Cross-source Insights
"Calculate ROAS by combining ad spend from Google Ads with revenue from Stripe"
Trend Detection
"Which product category has the highest refund rate this quarter?"
Automated Alerts
"Alert me if the 3-day conversion rate drops below 2%"
Data Cleanup
Push messy CSV exports and let Databox normalize dates, formats, and schemas automatically
- Databox MCP Landing Page
- Blog: Chat with Your Data Anywhere
- Model Context Protocol Specification
- Databox Help Center
For questions and support:
- Visit the Databox Help Center
- Contact support@databox.com
Built by Databox — Track all your business metrics in one place.