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

41.3/100 developing ▬ flat Agent 16/100 agent aware saas Full breakdown ↓
scored 2026-09-08 · rubric v0.20.0

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 2026-09-08 · rubric v0.20.0

Composite quality — 41.3/100 · developing

Contract Quality 12.2 / 25

Developer Ergonomics 3.8 / 20

Access Clarity 11.6 / 20

Operational Transparency 6.8 / 13

Contract Governance 0.0 / 12

Discoverability 6.9 / 10

Agent readiness — 16/100 · 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

Delegated User Identity 0 / 6

Protected Resource Metadata 0 / 5

Registration Without a Human 0 / 6

Agentic Commerce Well-Known Document 0 / 5

Create-or-Update Ergonomics could not be measured. We hold no machine-readable contract for this provider to read, so there is nothing to measure a write surface against. Excluded rather than scored zero: never-measured and measured-empty are different facts. Publishing an OpenAPI is what makes this facet — and several others — scorable at all.

Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. Every facet and dimension name above is a link: it opens that measurement's own page — what it means, the exact checks that feed it, how the whole catalog distributes on it, and the providers at the top of it. 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. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

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

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
deliveryModel:
  model: saas
  open_source: false
  commercial: true
  callable_host: false
  label: Hosted service · you call their endpoint
  confidence: medium
  source:
  - pricing
  generated: '2026-08-28'
  method: derived
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

Work with this as data

Every provider here is available over the APIs.io API and to AI agents over MCP.

MCP server

One button, every client — Claude, Cursor, VS Code and the rest.

https://apis.io/mcp

Tools for providers

9 MCP tools reach this

find_providersBrowse and filter every provider in the catalog.
get_provider_artifactsEvery artifact this provider publishes, grouped by type.
get_provider_operationsEvery operation across all of their OpenAPIs — one call instead of parsing every spec.
get_provider_toolsEvery MCP tool they ship, with the operation each wraps.
get_provider_evidenceHow each part of their score was established. Free — the basis for a claim should not sit behind it.
get_provider_ratingPRO — composite, band, trend and facet scores.
apis_io_searchSTART HERE — APIs, providers and tags for one query, each with its total.
resolveTurn a domain, URL or GitHub org into the provider it belongs to.
find_cohortsEvery scored population of providers in the catalog.

All 92 tools →

Call it yourself

curl for this page

This provider

curl "https://apis.io/api/v1/providers/montecarlodata"

All providers

curl "https://apis.io/api/v1/providers?limit=25"

Every operation they expose

curl "https://apis.io/api/v1/providers/montecarlodata/operations?limit=25"

How their score was established

curl "https://apis.io/api/v1/providers/montecarlodata/evidence"

Discovery needs no key. Ratings and market analysis are Pro.

Get an API key

Free tier, no form to fill in. Signing in shares your email address with us — we store it to create your key and to recognise you if you sign in with another provider. See our Privacy Policy and Terms.

GitHub Google LinkedIn

A second provider on the same verified email joins the account you already have.