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

40.4/100 developing ▬ flat Agent 18/100 agent aware Full breakdown ↓
scored 2026-08-21 · rubric v0.12.0

AccessPaid

1 APIs

Data Observability Data Quality Data Monitoring Data Lineage GraphQL AI Observability Data Reliability

Kin Score

Kin Score How this is scored →
scored 2026-08-21 · rubric v0.12.0

Composite quality — 40.4/100 · developing

Contract Quality 12.8 / 25

Developer Ergonomics 2.4 / 20

Access Clarity 11.6 / 20

Operational Transparency 6.8 / 13

Contract Governance 0.0 / 12

Discoverability 6.9 / 10

Agent readiness — 18/100 · agent aware

Machine-Readable Contract 18 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

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.

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.

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

Blog

Blog

Other 1

Properties that don't map to a standard resource type

Source (apis.yml)

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: '0.23'
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

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Monte Carlo

Kin Score

APIs 1

Monte Carlo GraphQL API

GraphQL 1

Monte Carlo Data GraphQL API

Pricing Plans 1

Montecarlodata Plans Pricing

Rate Limits 1

Montecarlodata Rate Limits

FinOps 1

Montecarlodata Finops

Semantic Vocabularies 1

Montecarlodata Context

Security Posture 2

Montecarlodata Domain Security

Montecarlodata Trust Center

Resources