# Marquez

**Canonical:** https://apis.io/providers/marquez/  
**Website:** https://marquezproject.ai  
**APIs profiled:** 1

Marquez Project provides an open-source metadata service that implements the OpenLineage specification. It enables organizations to collect, store, and visualize lineage metadata from various data processing tools such as Airflow, Spark, Flink, dbt, and Dagster. The platform offers a RESTful API, a web UI for visual graphs, and integrations with Slack and GitHub, helping teams improve data governance, quality monitoring, and performance analytics.

## Kin Score — 9.7 / 100 (minimal)

Scored 2026-11-06 under rubric 0.27.0. Trend: flat (-4.5 from 14.2).

| Facet | Score |
|---|---|
| Discoverability | 57.1 |
| Contract Quality | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 10.5 |
| Developer Ergonomics | 20.2 |
| Access Clarity | 0.0 |

Regulatory layer — **Horizontal (data, software, accessibility, platform)**: 5.9 (matched via fallback).

## Agent readiness — 0.0 (human-only)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| Reversibility Documented | no |
| MCP Server | no |
| Auth Clarity | no |
| Idempotency | no |
| Error Semantics | no |
| OpenAPI Examples | no |
| Rate Limit Signal | no |
| Event Surface Described | no |
| Agent Skills | no |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |
| Delegated Identity | no |
| Protected Resource Metadata | no |
| Dynamic Client Registration | no |
| Agentic Commerce | no |
| Pagination Ratio | na |
| Operation Distinctiveness | na |
| MCP Tool Quality | na |

## Access

Unknown — onboarding: unknown, pricing: unknown, trial: no (confidence: low).

## APIs (1)

- **Marquez API** — Open-source metadata service API

## Security (1)

- **Marquez Domain Security** — TLSv1.3

## Tags

Company, Open Source, Data Lineage, Metadata, OpenLineage

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Profiled by [API Evangelist](https://apievangelist.com) and published on [APIs.io](https://apis.io/providers/marquez/). Scores are computed from the provider's own public artifacts under a published rubric.