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.
Monte Carlo publishes 1 API on the APIs.io network: Graphql API. Tagged areas include Data Observability, Data Quality, Data Reliability, Data Lake, and Data Warehouse.
Monte Carlo’s developer surface includes authentication, documentation, pricing, signup flow, engineering blog, API reference, and 7 more developer resources.
Create-or-Update Ergonomics applies to this provider. This API accepts writes, so it
carries 10 points of the composite. It is scored from the published contracts
themselves: whether a caller can create-or-update in one call, whether the write accepts a key the caller already
holds, and whether the response says which branch ran. Without that, every write needs a search-and-branch in
front of it, and the first time that check is skipped a duplicate record is created.
Scored against the observed mean rather than raw — a provider at the catalog average is unchanged by this facet,
not penalised by it.
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/monte-carlo: open an issue to ask a question, or submit a pull request to add artifacts.
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GraphQL API for the Monte Carlo data observability platform. Provides programmatic access to monitors, incidents, assets, lineage, custom rules, warehouses, lakes, metastores, a...
A REST write API for pushing observability data into Monte Carlo from sources its pull-based collectors cannot reach. Three endpoints — POST /ingest/v1/metadata (table and view ...
A first-party, fully hosted Model Context Protocol server that gives AI agents direct access to Monte Carlo — investigating alerts, exploring assets and lineage, creating and tu...
GraphQL API for the Monte Carlo data observability platform. Provides programmatic access to monitors, incidents, assets, lineage, custom rules, warehouses, lakes, metastores, a...
aid: monte-carlo
name: Monte Carlo
description: 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.
type: Index
deliveryModel:
model: saas
open_source: false
commercial: true
callable_host: true
label: Hosted service · you call their endpoint
confidence: high
source:
- openapi
- pricing
generated: '2026-08-28'
method: derived
accessModel:
pricing: unknown
onboarding: unknown
trial: false
try_now: false
public: false
label: Unknown
confidence: low
source:
- authentication
- security
generated: '2026-09-03'
method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/monte-carlo.png
tags:
- Data Observability
- Data Quality
- Data Reliability
- Data Lake
- Data Warehouse
- Lineage
- Monitoring
- AI Observability
url: https://raw.githubusercontent.com/api-evangelist/monte-carlo/refs/heads/main/apis.yml
created: '2026-05-11'
modified: '2026-05-11'
specificationVersion: '0.23'
apis:
- aid: monte-carlo:graphql-api
name: Monte Carlo GraphQL API
description: GraphQL API for the Monte Carlo data observability platform. Provides programmatic access to monitors, incidents,
assets, lineage, custom rules, warehouses, lakes, metastores, and alerts. Authentication uses an account or personal API
Key ID and Token sent via the x-mcd-id and x-mcd-token headers (or as a Bearer token).
humanURL: https://docs.getmontecarlo.com/docs/api
baseURL: https://api.getmontecarlo.com/graphql
tags:
- Data Observability
- GraphQL
- Monitoring
- Data Quality
- Lineage
properties:
- type: Documentation
url: https://docs.getmontecarlo.com/docs/api
- type: Developer Resources
url: https://docs.getmontecarlo.com/docs/developer-resources
- type: Data Lakes Integration
url: https://docs.getmontecarlo.com/docs/data-lakes
- type: Python SDK (pycarlo)
url: https://github.com/monte-carlo-data/python-sdk
- type: CLI
url: https://github.com/monte-carlo-data/monte-carlo-cli
- type: MCP Server
url: https://docs.getmontecarlo.com/docs/mcp-server
- url: graphql/monte-carlo-graphql.md
type: GraphQL
- aid: monte-carlo:monte-carlo-graphql-api
name: Monte Carlo Graphql API
description: The Graphql API from Monte Carlo — 1 operation(s) for graphql.
humanURL: https://docs.getmontecarlo.com/docs/api
baseURL: https://api.getmontecarlo.com/graphql
tags:
- GraphQL
tags_raw:
- Graphql
properties:
- type: OpenAPI
url: openapi/monte-carlo-graphql-api-openapi.yml
- aid: monte-carlo:push-ingest-api
name: Monte Carlo Push Ingest API
description: A REST write API for pushing observability data into Monte Carlo from sources its pull-based collectors cannot
reach. Three endpoints — POST /ingest/v1/metadata (table and view schema, columns, row and byte counts, freshness), POST
/ingest/v1/lineage (table- and column-level lineage) and POST /ingest/v1/querylogs (SQL query history) — each returning
202 Accepted with an invocation_id. Requires a dedicated Ingestion-scoped integration key; standard API keys are rejected.
Public preview, Enterprise plan or higher.
humanURL: https://docs.getmontecarlo.com/docs/push-ingest-api
baseURL: https://integrations.getmontecarlo.com
tags:
- Data Observability
- Data Lineage
- Ingest
properties:
- type: Documentation
url: https://docs.getmontecarlo.com/docs/push-ingest-api
- type: ErrorCatalog
url: errors/monte-carlo-data-problem-types.yml
- aid: monte-carlo:mcp-server
name: Monte Carlo MCP Server
description: A first-party, fully hosted Model Context Protocol server that gives AI agents direct access to Monte Carlo
— investigating alerts, exploring assets and lineage, creating and tuning monitors, and evaluating AI agent performance.
56 documented tools across three toolsets (default, extended, agent_observability) plus four published MCP prompts. Reached
over streamable HTTP with OAuth 2.1 and dynamic client registration, or with MCP-scoped keys; also shipped as an Anthropic-verified
connector in the Claude Connectors Directory. Runs on AWS Lambda, stateless, executing under the calling user's Monte
Carlo identity.
humanURL: https://docs.getmontecarlo.com/docs/mcp-server
baseURL: https://mcp.getmontecarlo.com/mcp
tags:
- MCP
- Agent Observability
- AIOps
tags_raw:
- Model Context Protocol
- Agent Observability
- AIOps
properties:
- type: MCPServer
url: mcp/monte-carlo-data-mcp.yml
- type: ToolCrosswalk
url: mcp/monte-carlo-data-tool-crosswalk.yml
- type: Documentation
url: https://docs.getmontecarlo.com/docs/mcp-server
common:
- type: AgenticAccess
url: agentic-access/monte-carlo-agentic-access.yml
- type: TrustCenter
url: security/monte-carlo-trust-center.yml
- type: DomainSecurity
url: security/monte-carlo-domain-security.yml
- type: Authentication
url: authentication/monte-carlo-authentication.yml
- type: LinkedIn
url: https://www.linkedin.com/company/monte-carlo-data
- type: Website
url: https://www.montecarlodata.com
- type: Documentation
url: https://docs.getmontecarlo.com
- type: GitHubOrganization
url: https://github.com/monte-carlo-data
- type: Pricing
url: https://www.montecarlodata.com/pricing/
- type: Signup
url: https://www.montecarlodata.com/request-a-demo/
- type: LlmsText
url: https://docs.getmontecarlo.com/llms.txt
- url: https://montecarlodata.com/blog/feed/
type: Blog
- type: APIReference
url: https://apidocs.getmontecarlo.com/
maintainers:
- FN: Kin Lane
email: kin@apievangelist.com
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