curl --request GET \
     --url 'https://mdb.ai/api/datasources/datasource_name?check_connection=true' \
     --header 'Authorization: Bearer MINDS_API_KEY'
{
    "connection_data": {
        "database": "demo",
        "host": "samples.mindsdb.com",
        "password": "demo_password",
        "port": "5432",
        "schema": "demo_data",
        "user": "demo_user"
    },
    "connection_status": {
        "error_message": null,
        "success": true
    },
    "description": "House sales data",
    "engine": "postgres",
    "name": "my_datasource",
    "tables": ["house_sales"]
}

This API endpoint retrieves details about a specific Datasource using the GET method.

Body

check_connection
string

Set this value to true to check the connection to the data source.

Response

connection_data
object
required

Details for connecting to the data source including host, port, user, password, etc.

connection_status
object

The status of the connection test, if check_connection=true. Includes success flag and error message if applicable.

description
string

Optional description of the datasource.

engine
string
required

The engine type of the datasource (e.g., postgres).

name
string
required

The unique name of the datasource.

tables
array

List of tables that are accessible from this datasource.

Authorization

A valid API key must be passed in the Authorization header:

Authorization: Bearer MINDS_API_KEY

Generate your API key here.

Path Parameters

datasource_name
string
required

The name of the Datasource you want to retrieve.

curl --request GET \
     --url 'https://mdb.ai/api/datasources/datasource_name?check_connection=true' \
     --header 'Authorization: Bearer MINDS_API_KEY'
{
    "connection_data": {
        "database": "demo",
        "host": "samples.mindsdb.com",
        "password": "demo_password",
        "port": "5432",
        "schema": "demo_data",
        "user": "demo_user"
    },
    "connection_status": {
        "error_message": null,
        "success": true
    },
    "description": "House sales data",
    "engine": "postgres",
    "name": "my_datasource",
    "tables": ["house_sales"]
}