Cursor
Dinobase integrates with Cursor via MCP. Once connected, Cursor’s AI agent can query all your synced business data while you code.
Install
Section titled “Install”curl -fsSL https://dinobase.ai/install.sh | bash -s -- cursorInstalls Dinobase via uv, runs dinobase init, and writes CLI usage instructions to AGENTS.md in your current directory. Then connect your data sources:
dinobase add stripe --api-key sk_test_...dinobase add hubspot --api-key pat-...dinobase syncSee Connecting Sources for the full list of 100+ supported sources, and Syncing & Scheduling for background sync options.
Cursor’s agent can then run shell commands like dinobase info, dinobase describe stripe.customers, and dinobase query "SELECT ..." to answer questions about your data.
To re-run the setup step: dinobase install cursor from your project root (safe to run multiple times — replaces the existing block).
How it works
Section titled “How it works”The agent will:
- Run
dinobase infoto discover available data - Run
dinobase describe <table>to understand columns and types - Run
dinobase query "<sql>"to execute SQL (DuckDB dialect) - For mutations (UPDATE/INSERT),
queryreturns a preview — the agent runsdinobase confirm <id>to execute
Alternative: MCP server
Section titled “Alternative: MCP server”If you prefer MCP, run dinobase mcp-config cursor to get the JSON config, then add it to .cursor/mcp.json in your project root.
Available CLI commands
Section titled “Available CLI commands”| Command | Description |
|---|---|
dinobase info | Database overview — sources, tables, row counts |
dinobase describe <table> | Table schema, column types, and sample data |
dinobase query "<sql>" | Execute SQL queries (DuckDB dialect) |
dinobase refresh [source] | Re-sync a data source to get fresh data |
dinobase confirm <id> | Execute a pending mutation |
dinobase cancel <id> | Cancel a pending mutation |
Next steps
Section titled “Next steps”- Getting Started — Full setup walkthrough
- Connecting Sources — Add your business data
- Querying Data — SQL patterns and cross-source joins
- Syncing & Scheduling — Keep data fresh
- Schema Annotations — Add context for AI agents
- MCP Integration — How the MCP server works
- MCP Tools Reference — Detailed tool schemas