Databox MCP connector

1. Install the SDK

   Node.js

   npm install @scalekit-sdk/node

   Python

   pip install scalekit

   Full SDK reference: Node.js | Python

2. Set your credentials

   Add your Scalekit credentials to your .env file. Find values in app.scalekit.com > Developers > API Credentials.

   .env

   SCALEKIT_ENVIRONMENT_URL=<your-environment-url>
   SCALEKIT_CLIENT_ID=<your-client-id>
   SCALEKIT_CLIENT_SECRET=<your-client-secret>

3. Authorize and make your first call

   Node.js

   quickstart.ts

   import { ScalekitClient } from '@scalekit-sdk/node'
   import 'dotenv/config'
   
   const scalekit = new ScalekitClient(
     process.env.SCALEKIT_ENV_URL,
     process.env.SCALEKIT_CLIENT_ID,
     process.env.SCALEKIT_CLIENT_SECRET,
   )
   const actions = scalekit.actions
   
   const connector = 'databoxmcp'
   const identifier = 'user_123'
   
   // Generate an authorization link for the user
   const { link } = await actions.getAuthorizationLink({ connectionName: connector, identifier })
   console.log('Authorize Databox MCP:', link)
   process.stdout.write('Press Enter after authorizing...')
   await new Promise(r => process.stdin.once('data', r))
   
   // Make your first call
   const result = await actions.executeTool({
     connector,
     identifier,
     toolName: 'databoxmcp_get_current_datetime',
     toolInput: {},
   })
   console.log(result)

   Python

   quickstart.py

   import os
   from scalekit.client import ScalekitClient
   from dotenv import load_dotenv
   load_dotenv()
   
   scalekit_client = ScalekitClient(
       env_url=os.getenv("SCALEKIT_ENV_URL"),
       client_id=os.getenv("SCALEKIT_CLIENT_ID"),
       client_secret=os.getenv("SCALEKIT_CLIENT_SECRET"),
   )
   actions = scalekit_client.actions
   
   connection_name = "databoxmcp"
   identifier = "user_123"
   
   # Generate an authorization link for the user
   link_response = actions.get_authorization_link(
       connection_name=connection_name,
       identifier=identifier,
   )
   print("Authorize Databox MCP:", link_response.link)
   input("Press Enter after authorizing...")
   
   # Make your first call
   result = actions.execute_tool(
       tool_input={},
       tool_name="databoxmcp_get_current_datetime",
       connection_name=connection_name,
       identifier=identifier,
   )
   print(result)

What you can do

Connect this agent connector to let your agent:

• Data load metric, ingest — Retrieve data points for a Databox metric over a date range with optional time-series granulation and dimension breakdown
• List metrics, merged datasets, data sources — List all metrics available for a Databox data source, including metric keys, names, descriptions, and available dimensions
• Get ingestion, dataset ingestions, current datetime — Get detailed information for a specific ingestion event, including status, timestamps, dataset metrics, and per-record ingestion outcomes
• Delete dataset, data source — Permanently delete a dataset and all its data from Databox
• Create dataset, data source — Create a structured dataset within a Databox data source, optionally defining a column schema and primary keys for tabular data storage
• Genie ask — Ask Genie, the Databox AI data analyst, to explore and analyze a dataset using natural language

Tool list

Use the exact tool names from the Tool list below when you call execute_tool. If you’re not sure which name to use, list the tools available for the current user first.

databoxmcp_ask_genie # Ask Genie, the Databox AI data analyst, to explore and analyze a dataset using natural language. Genie can answer business questions, run SQL queries, surface trends, and provide summaries. 3 params ▾

Ask Genie, the Databox AI data analyst, to explore and analyze a dataset using natural language. Genie can answer business questions, run SQL queries, surface trends, and provide summaries.

Name Type Required Description

dataset_id string required No description.

question string required No description.

thread_id string optional No description.

databoxmcp_create_data_source # Create a new data source container in Databox for organizing datasets. Optionally scopes the data source to a specific account; defaults to the account of the authenticated API key. 2 params ▾

Create a new data source container in Databox for organizing datasets. Optionally scopes the data source to a specific account; defaults to the account of the authenticated API key.

Name Type Required Description

name string required No description.

account_id string optional No description.

databoxmcp_create_dataset # Create a structured dataset within a Databox data source, optionally defining a column schema and primary keys for tabular data storage. 4 params ▾

Create a structured dataset within a Databox data source, optionally defining a column schema and primary keys for tabular data storage.

Name Type Required Description

data_source_id string required No description.

name string required No description.

columns string optional No description.

primary_keys string optional No description.

databoxmcp_delete_data_source # Permanently delete a data source and all its associated datasets from Databox. This operation cannot be undone. 1 param ▾

Permanently delete a data source and all its associated datasets from Databox. This operation cannot be undone.

Name Type Required Description

data_source_id string required No description.

databoxmcp_delete_dataset # Permanently delete a dataset and all its data from Databox. This operation cannot be undone. 1 param ▾

Permanently delete a dataset and all its data from Databox. This operation cannot be undone.

Name Type Required Description

dataset_id string required No description.

databoxmcp_get_current_datetime # Get the current date and time in ISO 8601 format for a given timezone. Useful for resolving relative date expressions such as "last month" or "yesterday" before passing absolute dates to other tools. 1 param ▾

Get the current date and time in ISO 8601 format for a given timezone. Useful for resolving relative date expressions such as "last month" or "yesterday" before passing absolute dates to other tools.

Name Type Required Description

timezone string optional No description.

databoxmcp_get_dataset_ingestions # Retrieve the full ingestion history for a dataset, including job IDs, statuses, record counts, timestamps, and any error messages. 1 param ▾

Retrieve the full ingestion history for a dataset, including job IDs, statuses, record counts, timestamps, and any error messages.

Name Type Required Description

dataset_id string required No description.

databoxmcp_get_ingestion # Get detailed information for a specific ingestion event, including status, timestamps, dataset metrics, and per-record ingestion outcomes. 2 params ▾

Get detailed information for a specific ingestion event, including status, timestamps, dataset metrics, and per-record ingestion outcomes.

Name Type Required Description

dataset_id string required No description.

ingestion_id string required No description.

databoxmcp_ingest_data # Push data records into an existing Databox dataset. Each record must match the dataset schema; data is validated against column types and constraints before ingestion. 2 params ▾

Push data records into an existing Databox dataset. Each record must match the dataset schema; data is validated against column types and constraints before ingestion.

Name Type Required Description

data string required No description.

dataset_id string required No description.

databoxmcp_list_accounts # List all Databox accounts accessible to the authenticated user. Use this to discover account IDs needed for other operations. 0 params ▾

List all Databox accounts accessible to the authenticated user. Use this to discover account IDs needed for other operations.

databoxmcp_list_data_source_datasets # List all datasets belonging to a specific Databox data source, including schema details, row counts, and metadata. 1 param ▾

List all datasets belonging to a specific Databox data source, including schema details, row counts, and metadata.

Name Type Required Description

data_source_id string required No description.

databoxmcp_list_data_sources # List all API-ingestible data sources for a specific Databox account, returning IDs, names, types, and creation timestamps. 1 param ▾

List all API-ingestible data sources for a specific Databox account, returning IDs, names, types, and creation timestamps.

Name Type Required Description

account_id string required No description.

databoxmcp_list_merged_datasets # List all merged datasets for a specific Databox account. Merged datasets combine data from multiple sources into a single unified dataset. 1 param ▾

List all merged datasets for a specific Databox account. Merged datasets combine data from multiple sources into a single unified dataset.

Name Type Required Description

account_id string required No description.

databoxmcp_list_metrics # List all metrics available for a Databox data source, including metric keys, names, descriptions, and available dimensions. Pass the full metric_key value unchanged to load_metric_data. 1 param ▾

List all metrics available for a Databox data source, including metric keys, names, descriptions, and available dimensions. Pass the full metric_key value unchanged to load_metric_data.

Name Type Required Description

data_source_id integer required No description.

databoxmcp_load_metric_data # Retrieve data points for a Databox metric over a date range with optional time-series granulation and dimension breakdown. The metric_key must be the exact value returned by list_metrics. 8 params ▾

Retrieve data points for a Databox metric over a date range with optional time-series granulation and dimension breakdown. The metric_key must be the exact value returned by list_metrics.

Name Type Required Description

data_source_id integer required No description.

end_date string required No description.

metric_key string required No description.

start_date string required No description.

dimension string optional No description.

granulation_time_unit string optional No description.

is_whole_range boolean optional No description.

record_limit string optional No description.