Databox MCP turns Databox into an AI-native analytics backend. It removes the need for traditional BI steps (no warehouses, no manual dashboards) — your AI assistant can directly ingest data and query insights on the fly, all through one endpoint.
Databox MCP is a Model Context Protocol (MCP) server that connects your AI tools to your Databox data. It provides a standardized way for AI applications (like ChatGPT, Claude, or custom agents) to ingest data into Databox and query it using natural language. In essence, Databox MCP turns Databox into a two-way data pipeline: you can push any data source into Databox, and then have AI analyze that data to return insights — all through a single, open interface.
The Databox MCP server is under active development. Some functions and settings may not be available, and you may experience bugs or performance issues during this period. This feature continues to evolve and might be subject to rate limits.
Built on the open MCP specification, the Databox MCP server uses JSON-RPC over HTTP to communicate with AI clients. Under the hood, it integrates with the Databox Public API and the Databox analytics engine ("Agentic" AI system) to store incoming data and run analyses. This means the AI is working with the same governed, secure data in your Databox account, using your existing data permissions and structures. There's no need to manually set up dashboards or write SQL — you can ask questions in plain English, and the AI will handle data retrieval, transformation, and analysis.
https://mcp.databox.com/mcp
Key features include:
Natural Language Queries: Ask questions about your metrics or datasets in plain English. The MCP server's AI agent understands your schema, generates the necessary queries, and explains results in human-readable terms.
Unified Data Ingestion: Push data from any source (APIs, CSV files, databases, etc.) directly into Databox via the AI. The MCP's ingest_data tool can fetch and transform raw data automatically, then load it into Databox without manual ETL.
Real-Time Analysis and Insights: Once data is in Databox, you can immediately analyze it using query_dataset_with_ai. The AI will apply relevant calculations (filters, aggregations, joins, etc.) and even detect trends or anomalies, providing explanations for its findings.
Standardized Protocol: Because it uses the MCP standard, Databox MCP works with any compliant client or AI platform. This includes popular tools like Anthropic Claude, OpenAI ChatGPT (developer mode), Cursor editor, as well as custom scripts using MCP SDKs.