Databox MCP

by databox

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About

The Databox MCP server empowers your AI tools to talk to your data, enabling agentic analytics, automated data ingestion, and real-time conversational analytics. It transforms Databox into an intelligent backend for your LLMs, allowing tools like ChatGPT, Claude and Cursor to que

Details

Author: databox
Downloads: 405
Categories: Cloud Service, Infrastructure, AI

- Query live metrics from 100+ integrations (Google Analytics, HubSpot, Stripe, and more)
- Analyze trends, anomalies, and correlations across data sources
- Generate reports and insights through natural language prompts
- Access KPIs and dashboards without leaving your AI tool
- Ingest and push custom data into Databox

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name Databox MCP

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "databox mcp": {
            "databox": {
                "command": "npx",
                "args": [
                    "-y",
                    "@databox/mcp-server"
                ],
                "env": {
                    "DATABOX_API_TOKEN": "your-api-token"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "databox mcp": {
            "databox": {
                "command": "npx",
                "args": [
                    "-y",
                    "@databox/mcp-server"
                ],
                "env": {
                    "DATABOX_API_TOKEN": "your-api-token"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "databox mcp": {
            "databox": {
                "command": "npx",
                "args": [
                    "-y",
                    "@databox/mcp-server"
                ],
                "env": {
                    "DATABOX_API_TOKEN": "your-api-token"
                }
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "databox mcp": {
            "databox": {
                "command": "npx",
                "args": [
                    "-y",
                    "@databox/mcp-server"
                ],
                "env": {
                    "DATABOX_API_TOKEN": "your-api-token"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "databox mcp": {
            "databox": {
                "command": "npx",
                "args": [
                    "-y",
                    "@databox/mcp-server"
                ],
                "env": {
                    "DATABOX_API_TOKEN": "your-api-token"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "databox mcp": {
            "databox": {
                "command": "npx",
                "args": [
                    "-y",
                    "@databox/mcp-server"
                ],
                "env": {
                    "DATABOX_API_TOKEN": "your-api-token"
                }
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "databox mcp": {
            "databox": {
                "command": "npx",
                "args": [
                    "-y",
                    "@databox/mcp-server"
                ],
                "env": {
                    "DATABOX_API_TOKEN": "your-api-token"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "databox mcp": {
            "databox": {
                "command": "npx",
                "args": [
                    "-y",
                    "@databox/mcp-server"
                ],
                "env": {
                    "DATABOX_API_TOKEN": "your-api-token"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "databox mcp": {
            "databox": {
                "command": "npx",
                "args": [
                    "-y",
                    "@databox/mcp-server"
                ],
                "env": {
                    "DATABOX_API_TOKEN": "your-api-token"
                }
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "databox mcp": {
            "databox": {
                "command": "npx",
                "args": [
                    "-y",
                    "@databox/mcp-server"
                ],
                "env": {
                    "DATABOX_API_TOKEN": "your-api-token"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "databox mcp": {
            "databox": {
                "command": "npx",
                "args": [
                    "-y",
                    "@databox/mcp-server"
                ],
                "env": {
                    "DATABOX_API_TOKEN": "your-api-token"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "databox mcp": {
            "databox": {
                "command": "npx",
                "args": [
                    "-y",
                    "@databox/mcp-server"
                ],
                "env": {
                    "DATABOX_API_TOKEN": "your-api-token"
                }
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "databox mcp": {
            "databox": {
                "command": "npx",
                "args": [
                    "-y",
                    "@databox/mcp-server"
                ],
                "env": {
                    "DATABOX_API_TOKEN": "your-api-token"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "databox mcp": {
            "databox": {
                "command": "npx",
                "args": [
                    "-y",
                    "@databox/mcp-server"
                ],
                "env": {
                    "DATABOX_API_TOKEN": "your-api-token"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "databox mcp": {
            "databox": {
                "command": "npx",
                "args": [
                    "-y",
                    "@databox/mcp-server"
                ],
                "env": {
                    "DATABOX_API_TOKEN": "your-api-token"
                }
            }
        }
    }
}

From the repository

Connect your Databox account using your API token (found at app.databox.com/account/profile). Once connected, ask your AI tool questions about your business data—such as marketing performance or revenue trends—without building dashboards or writing queries.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "databox mcp": {
            "databox": {
                "command": "npx",
                "args": [
                    "-y",
                    "@databox/mcp-server"
                ],
                "env": {
                    "DATABOX_API_TOKEN": "your-api-token"
                }
            }
        }
    }
}

McpServers

{
    "databox": {
        "command": "npx",
        "args": [
            "-y",
            "@databox/mcp-server"
        ],
        "env": {
            "DATABOX_API_TOKEN": "your-api-token"
        }
    }
}

- Ask natural-language questions about your data— useask_genieto get calculated answers from a dataset, with optional conversation threading for follow-ups.
- Retrieve metric values over time— callload_metric_datato pull a specific metric for a date range, optionally broken down by a dimension or granulated by hour/day/week/month.
- Discover available metrics and data sources— uselist_metricsandlist_data_sourcesto see what’s already connected in an account before querying.
- Push custom data into Databox— create a data source and dataset withcreate_data_sourceandcreate_dataset, then load records viaingest_data.
- Inspect ingestion history— useget_dataset_ingestionsandget_ingestionto review record counts and details of past data loads.
- Resolve relative dates accurately— callget_current_datetimeto anchor phrases like “last month” before passing dates to other tools.

Databox MCP is aModel Context Protocolserver 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.

- Query your data using natural language
- Works with 130+ existing Databox integrations
- No additional cost for Databox users
- Setup in under 60 seconds

Add to yourclaude_desktop_config.json:

{ "mcpServers": { "databox": { "type": "http", "url": "https://mcp.databox.com/mcp" } } }

- Go toSettings→Connectors
- ClickAdd 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 URLhttps://mcp.databox.com/mcp.

Use anHTTP Requestnode pointing tohttps://mcp.databox.com/mcpand build your workflows from there.

Databox MCP exposes 15 tools for interacting with your data:

List all Databox accounts accessible to the authenticated user.

List all data sources for a specific account.

Create a new data source container for organizing datasets.

Permanently remove a data source and all its associated datasets. Cannot be undone.

List all datasets belonging to a specific data source.

Create a new dataset within a data source, with an optional schema.

Push data records into an existing dataset.

Get ingestion history for a specific dataset.

Get detailed information for a specific ingestion event, including record counts and dataset metrics.

Permanently remove a dataset and all its data. Cannot be undone.

List all merged datasets for a specific account. Merged datasets combine data from multiple sources.

List all metrics available for a data source (Google Analytics, Stripe, etc.).

Load data for a metric over a date range with optional dimensions and time-series granulation.

Query your data using natural language, powered by Genie AI. Genie executes actual queries against your data and returns calculated results, not LLM approximations. Supports conversation threading for follow-up questions.

Get the current date and time. Use this to resolve relative date expressions like "last month" or "yesterday" before calling other tools.

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.

- OAuth 2.0for user authorization
- JWT token validationfor secure sessions
- API key authenticationfor 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

"What was our conversion rate last week compared to the previous week?"

"Calculate ROAS by combining ad spend from Google Ads with revenue from Stripe"

"Which product category has the highest refund rate this quarter?"

"Alert me if the 3-day conversion rate drops below 2%"

Push messy CSV exports and let Databox normalize dates, formats, and schemas automatically

"Show me Google Analytics sessions for the last 30 days broken down by traffic source"

"Load daily page views for January with weekly aggregation"

"What are the top 10 countries by revenue from Stripe?"

- Databox MCP Landing Page
- Blog: Chat with Your Data Anywhere
- Model Context Protocol Specification
- Databox Help Center

- Visit the Databox Help Center
- Contact support@databox.com

Built by Databox— Track all your business metrics in one place.

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Databox MCP

About

Details

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Setting up with Highlight

Setting up with Cursor

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Setting up with Claude Desktop

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Setting up with Windsurf

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Setting up with Cline

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Setting up with Goose

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From the repository

Claude Desktop / Cursor

McpServers

Bastion: External Attack Surface Monitoring

Install

About

Details

Jump to

Setting up with Highlight

From the repository

Claude Desktop / Cursor

McpServers

Bastion: External Attack Surface Monitoring

Install

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