Monte Carlo website screenshot

Monte Carlo

Monte Carlo is a data and AI observability platform that helps enterprise organizations find and fix bad data fast. The platform exposes a GraphQL API that powers all the same capabilities as the Monte Carlo web application, enabling programmatic management of data monitors, incidents, field health, and lineage across data warehouses, lakes, ETL, and BI. Developers can automate custom monitoring configurations, augment lineage with external resources, manage bulk operations, and push metadata from sources unreachable via standard collection through the Push Ingest API. Additional developer tools include a Python SDK (Pycarlo), a CLI for onboarding and integration operations, webhooks for routing incident data to custom platforms, and an Airflow provider for pipeline quality gates.

Monte Carlo publishes 1 API on the APIs.io network: GraphQL API. Tagged areas include Data Observability, Data Quality, Data Monitoring, Data Lineage, and GraphQL.

The Monte Carlo catalog on APIs.io includes 1 JSON-LD context.

Monte Carlo’s developer surface includes documentation, engineering blog, pricing, and 10 more developer resources.

🌐 Visit website 📡 Source on GitHub
41.6/100 thin ▬ flat Agent 19/100 agent aware Full breakdown ↓
scored 2026-07-28 · rubric v0.6
AccessPaid
1 APIs
Data ObservabilityData QualityData MonitoringData LineageGraphQLAI ObservabilityData Reliability

Kin Score

Kin Score Kin Score How this is scored →
scored 2026-07-28 · rubric v0.6
Composite quality — 41.6/100 · thin
Contract Quality 14.2 / 25
Developer Ergonomics 2.2 / 20
Commercial Clarity 11.6 / 20
Operational Transparency 6.8 / 13
Governance 0.0 / 12
Discoverability 6.9 / 10
Agent readiness — 19/100 · agent aware
Machine-Readable Contract 18 / 18
Agentic Access Contract 0 / 10
MCP Server 0 / 12
Machine-Readable Auth 0 / 10
Idempotency 0 / 9
Stable Error Semantics 0 / 8
Request/Response Examples 0 / 7
Rate-Limit Signaling 7 / 7
Typed Event Surface 0 / 6
Agent Skills 0 / 5
Well-Known Catalog 0 / 4
Consent & Bot Identity 0 / 3
A2A Agent Card 0 / 8
Dry-Run / Simulate Mode 0 / 4
Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. This rating is computed from github.com/api-evangelist/montecarlodata: open an issue to ask a question, or submit a pull request to add artifacts. Want it done for you? Prioritized profiling — $2,500 →

APIs 1

Individual APIs this provider publishes, each with its own machine-readable definition.

Monte Carlo GraphQL API

GraphQL API powering the full Monte Carlo platform, enabling programmatic access to data monitors, incidents, field health, lineage, table and warehouse asset management, and th...

GraphQL 1

GraphQL schemas published by this provider.

Monte Carlo Data GraphQL API

Monte Carlo Data exposes a comprehensive GraphQL API that powers the full Monte Carlo data observability platform. The API provides programmatic access to all platform capabilit...

GRAPHQL

Pricing Plans 1

Published pricing tiers and plan structures.

Montecarlodata Plans Pricing

3 plans

PLANS

Rate Limits 1

Documented rate limits and quota policies.

Montecarlodata Rate Limits

3 limits

RATE LIMITS

FinOps 1

Cost, billing, and metering signals for API financial operations.

Montecarlodata Finops

FINOPS

Semantic Vocabularies 1

JSON-LD contexts and semantic vocabularies used across these APIs.

Montecarlodata Context

11 classes · 11 properties

JSON-LD

Security Posture 2

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Montecarlodata Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Montecarlodata Trust Center

SOC 2, ISO 27001

SECURITY

Resources

Documentation 1

Reference material describing how the API behaves

Documentation
Documentation

Build 1

SDKs, sample code, and the tooling you integrate with

GitHubOrg
GitHubOrg

Access & Security 2

Authentication, authorization, and security posture

TrustCenter
TrustCenter
 DomainSecurity
DomainSecurity

Operate 2

Status, limits, changes, and where to get help

StatusPage
StatusPage
 RateLimits
RateLimits

Commercial 3

Pricing, plans, and the legal terms of use

Pricing
Pricing
 Plans
Plans
 FinOps
FinOps

Company 3

The organization behind the API

Website
Website
 LinkedIn
LinkedIn
 Blog
Blog

Other 1

Properties that don't map to a standard resource type

X
X

Source (apis.yml)

apis.yml Raw ↑ 
aid: montecarlodata
name: Monte Carlo
description: 'Monte Carlo is a data and AI observability platform that helps enterprise organizations find and fix bad data
  fast. The platform exposes a GraphQL API that powers all the same capabilities as the Monte Carlo web application, enabling
  programmatic management of data monitors, incidents, field health, and lineage across data warehouses, lakes, ETL, and BI.
  Developers can automate custom monitoring configurations, augment lineage with external resources, manage bulk operations,
  and push metadata from sources unreachable via standard collection through the Push Ingest API. Additional developer tools
  include a Python SDK (Pycarlo), a CLI for onboarding and integration operations, webhooks for routing incident data to custom
  platforms, and an Airflow provider for pipeline quality gates.

  '
type: Index
accessModel:
  pricing: paid
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Paid
  confidence: medium
  source:
  - plans
  generated: '2026-07-22'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/montecarlodata.png
url: https://raw.githubusercontent.com/api-evangelist/montecarlodata/refs/heads/main/apis.yml
created: '2026-06-13'
modified: '2026-06-13'
specificationVersion: '0.19'
tags:
- Data Observability
- Data Quality
- Data Monitoring
- Data Lineage
- GraphQL
- AI Observability
- Data Reliability
apis:
- name: Monte Carlo GraphQL API
  description: 'GraphQL API powering the full Monte Carlo platform, enabling programmatic access to data monitors, incidents,
    field health, lineage, table and warehouse asset management, and the Push Ingest API for custom metadata ingestion from
    sources unreachable via standard pull-based collection.

    '
  image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/apis-json-logo.jpg
  humanURL: https://docs.getmontecarlo.com/docs/api
  baseURL: https://api.getmontecarlo.com/graphql
  tags:
  - Data Observability
  - GraphQL
  - Data Monitoring
  - Data Lineage
  properties:
  - type: Documentation
    url: https://docs.getmontecarlo.com/docs/api
  - type: APIReference
    url: https://apidocs.getmontecarlo.com
  - type: OpenAPI
    url: https://apidocs.getmontecarlo.com
  - url: graphql/montecarlodata-graphql.md
    type: GraphQL
common:
- type: TrustCenter
  url: security/montecarlodata-trust-center.yml
- type: DomainSecurity
  url: security/montecarlodata-domain-security.yml
- type: Website
  url: https://montecarlo.ai
- type: Documentation
  url: https://docs.getmontecarlo.com/docs/developer-resources
- type: GitHubOrg
  url: https://github.com/monte-carlo-data
- type: LinkedIn
  url: https://www.linkedin.com/company/monte-carlo-data
- type: Blog
  url: https://montecarlo.ai/blog
- type: Pricing
  url: https://info.montecarlodata.com/solutions/data-observability-platform-pricing
- type: StatusPage
  url: https://status.getmontecarlo.com
- type: X
  url: https://x.com/montecarlodata
- type: Plans
  url: plans/montecarlodata-plans-pricing.yml
- type: RateLimits
  url: rate-limits/montecarlodata-rate-limits.yml
- type: FinOps
  url: finops/montecarlodata-finops.yml
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com