Monte Carlo

Monte Carlo is a data and AI observability platform that monitors data warehouses, lakes, and pipelines for freshness, volume, schema, and quality anomalies, helping data teams detect, resolve, and prevent data downtime across Snowflake, Databricks, BigQuery, Redshift, and other modern data stack tools. Monte Carlo exposes a GraphQL API at https://api.getmontecarlo.com/graphql used for programmatic access to monitors, incidents, lineage, assets, alerts, custom rules, and lake/metastore integrations, with a supporting Python SDK and CLI (pycarlo / montecarlo). Authentication uses an API Key ID and Token pair sent via headers.

1 APIs 0 Features

Data ObservabilityData QualityData ReliabilityData LakeData WarehouseLineageMonitoringAI Observability

GitHubOrganization

Sources

opencollection: 1.0.0
info:
  name: Monte Carlo GraphQL API
  version: v1
request:
  auth:
    type: apikey
    key: x-mcd-id
    value: '{{x-mcd-id}}'
    placement: header
items:
- info:
    name: GraphQL endpoint
    type: http
  http:
    method: POST
    url: https://api.getmontecarlo.com/graphql
    body:
      type: json
      data: '{}'
  docs: 'Execute a GraphQL query or mutation against Monte Carlo. Common

    operations include `getUser`, `getTables`, `getMonitor`,

    `getIncidents`, and `createOrUpdateMonitor`. To discover the exact

    operations powering a given Monte Carlo UI view, inspect the network

    requests issued by that page.

    '
bundled: true

Monte Carlo

APIs

Monte Carlo GraphQL API

Collections

Monte Carlo GraphQL API

GraphQL

Monte Carlo GraphQL API

Resources

Sources