Bigeye is an enterprise data observability and AI trust platform that monitors data quality, detects schema changes and anomalies, classifies sensitive data, and maps column-level lineage across warehouses, lakes, BI tools and ETL pipelines. The platform combines automated data quality monitoring, ML-powered anomaly detection and lineage-based root-cause and downstream-impact analysis so teams can find and resolve data issues before they reach dashboards, reports or AI systems. Bigeye is API-first: its REST API is published as three OpenAPI 3.0 definitions (Metadata, Observability and Sensitivity) covering 263 operations, and it ships a first-party Python SDK, a Python CLI, Airflow operators, YAML-based observability-as-code configuration, and a hosted Model Context Protocol gateway that exposes 56 agent tools over the same platform.
Bigeye publishes 3 APIs on the APIs.io network: Metadata API, Observability API, and Sensitivity API. Tagged areas include Company, Data Observability, Data Quality, Data Lineage, and Data Governance.
The Bigeye catalog on APIs.io includes 1 event-driven AsyncAPI specification.
Bigeye’s developer surface includes authentication, documentation, API reference, getting-started guide, support, engineering blog, signup flow, and 30 more developer resources.
The Bigeye Metadata API covers the data catalog and workspace administration surface: sources, schemas, tables, columns and virtual tables; catalog rebuilds and schema-change tr...
The Bigeye Observability API covers monitoring and data quality: metrics (monitors) and metric templates, custom SQL rules, autometrics, backfills and batch metric runs, collect...
The Bigeye Sensitivity API covers sensitive data discovery and classification: classifiers, data classes and data class categories, scan jobs and scan job configuration, scan ru...
The Bigeye MCP Gateway is a hosted Model Context Protocol server at https://mcpgateway.bigeye.com/mcp that exposes 56 tools over the Bigeye platform for AI assistants and agents...
aid: bigeye
name: Bigeye
description: 'Bigeye is an enterprise data observability and AI trust platform that monitors data quality, detects schema
changes and anomalies, classifies sensitive data, and maps column-level lineage across warehouses, lakes, BI tools and ETL
pipelines. The platform combines automated data quality monitoring, ML-powered anomaly detection and lineage-based root-cause
and downstream-impact analysis so teams can find and resolve data issues before they reach dashboards, reports or AI systems.
Bigeye is API-first: its REST API is published as three OpenAPI 3.0 definitions (Metadata, Observability and Sensitivity)
covering 263 operations, and it ships a first-party Python SDK, a Python CLI, Airflow operators, YAML-based observability-as-code
configuration, and a hosted Model Context Protocol gateway that exposes 56 agent tools over the same platform.'
url: https://raw.githubusercontent.com/api-evangelist/bigeye/refs/heads/main/apis.yml
image: https://cdn.prod.website-files.com/64b205c9041f2a26ac7cb23f/69135c34ecede8d3fb8c6be8_bigeye-logo-1200x1200.jpg
x-type: company
x-source: harvest:secondary-market
specificationVersion: '0.20'
created: '2026-08-02'
modified: '2026-08-02'
tags:
- Company
- Data Observability
- Data Quality
- Data Lineage
- Data Governance
- Metadata Management
- Data Catalog
- Sensitive Data Discovery
- Monitoring
- Analytics
- AI Trust
- Snowflake
- Databricks
apis:
- aid: bigeye:bigeye-metadata-api
name: Bigeye Metadata API
description: 'The Bigeye Metadata API covers the data catalog and workspace administration surface: sources, schemas, tables,
columns and virtual tables; catalog rebuilds and schema-change tracking; lineage (v1 and v2) nodes and edges; users, groups,
roles, workspaces and object ownership; agent registration, API keys and service accounts; integrations, named schedules,
tags, favorites, search, dashboards and workflow status.'
humanURL: https://docs.bigeye.com/reference
baseURL: https://app.bigeye.com
tags:
- Catalog
- Metadata
- Lineage
- Schemas
- Tables
- Columns
- Sources
- Workspaces
- Users
- API Keys
properties:
- type: OpenAPI
url: openapi/bigeye-metadata-openapi.json
- type: Documentation
url: https://docs.bigeye.com/docs/api-user-guide
- type: APIReference
url: https://docs.bigeye.com/reference
- type: Overlay
url: overlays/bigeye-metadata-overlay.yaml
- aid: bigeye:bigeye-observability-api
name: Bigeye Observability API
description: 'The Bigeye Observability API covers monitoring and data quality: metrics (monitors) and metric templates,
custom SQL rules, autometrics, backfills and batch metric runs, collections of monitors, deltas and comparison tables
for cross-source validation, joins, observed columns, data quality dimensions, and the issue lifecycle including merging
issues into incidents.'
humanURL: https://docs.bigeye.com/reference
baseURL: https://app.bigeye.com
tags:
- Monitoring
- Metrics
- Data Quality
- Issues
- Incidents
- Collections
- Deltas
- Custom Rules
- Dimensions
properties:
- type: OpenAPI
url: openapi/bigeye-observability-openapi.json
- type: Documentation
url: https://docs.bigeye.com/docs/monitoring
- type: APIReference
url: https://docs.bigeye.com/reference
- type: Overlay
url: overlays/bigeye-observability-overlay.yaml
- aid: bigeye:bigeye-sensitivity-api
name: Bigeye Sensitivity API
description: 'The Bigeye Sensitivity API covers sensitive data discovery and classification: classifiers, data classes and
data class categories, scan jobs and scan job configuration, scan runs, and the aggregate and snapshot findings that report
where PII and other sensitive data was detected across connected sources.'
humanURL: https://docs.bigeye.com/reference
baseURL: https://app.bigeye.com
tags:
- Sensitive Data
- Classification
- PII
- Scanning
- Data Governance
properties:
- type: OpenAPI
url: openapi/bigeye-sensitivity-openapi.json
- type: Documentation
url: https://docs.bigeye.com/docs/getting-started-scanning
- type: APIReference
url: https://docs.bigeye.com/reference
- type: Overlay
url: overlays/bigeye-sensitivity-overlay.yaml
- aid: bigeye:bigeye-mcp-gateway
name: Bigeye MCP Gateway
description: The Bigeye MCP Gateway is a hosted Model Context Protocol server at https://mcpgateway.bigeye.com/mcp that
exposes 56 tools over the Bigeye platform for AI assistants and agents — listing and triaging data quality issues, searching
the catalog, tracing lineage, profiling tables, managing metrics, dimensions and tags, and reading sensitive-data scan
findings. Authentication uses the same Bigeye API key passed as an "apikey" prefixed Authorization header plus an x-bigeye-workspace-id
header. Public beta since July 2026; the server is also open source and self-hostable.
humanURL: https://docs.bigeye.com/docs/bigeye-mcp-server
baseURL: https://mcpgateway.bigeye.com/mcp
tags:
- MCP
- Agents
- AI
properties:
- type: MCPServer
url: mcp/bigeye-mcp.yml
- type: ToolCrosswalk
url: mcp/bigeye-tool-crosswalk.yml
- type: Documentation
url: https://docs.bigeye.com/docs/bigeye-mcp-server
- type: SourceCode
url: https://github.com/bigeyedata/bigeye-mcp-server
maintainers:
- FN: Kin Lane
email: kin@apievangelist.com
- FN: APIs.json
email: info@apis.io
common:
- type: AgenticAccess
url: agentic-access/bigeye-agentic-access.yml
- type: TrustCenter
url: security/bigeye-trust-center.yml
- type: VulnerabilityDisclosure
url: security/bigeye-vulnerability-disclosure.yml
- type: DomainSecurity
url: security/bigeye-domain-security.yml
- type: Authentication
url: authentication/bigeye-authentication.yml
- type: Website
url: https://www.bigeye.com/
- type: DeveloperPortal
url: https://docs.bigeye.com/
- type: Documentation
url: https://docs.bigeye.com/docs/api-user-guide
- type: APIReference
url: https://docs.bigeye.com/reference
- type: GettingStarted
url: https://docs.bigeye.com/docs/getting-started
- type: Support
url: https://www.bigeye.com/contact-us
- type: Blog
url: https://www.bigeye.com/blog
- type: GitHubOrganization
url: https://github.com/bigeyedata
- type: SignUp
url: https://app.bigeye.com/login
- type: TermsOfService
url: https://www.bigeye.com/terms/terms-of-use
- type: PrivacyPolicy
url: https://www.bigeye.com/privacy
- type: StatusPage
url: https://status.bigeye.com/
- type: Compliance
url: https://docs.bigeye.com/docs/security-and-compliance
- type: ChangeLog
url: https://docs.bigeye.com/docs/release-notes
- type: MCPServer
url: mcp/bigeye-mcp.yml
- type: WellKnown
url: well-known/bigeye-well-known.yml
- type: APICatalog
url: well-known/bigeye-api-catalog.json
- type: LLMsTxt
url: llms/bigeye-llms.txt
- type: Packages
url: packages/bigeye-packages.yml
- type: SDKs
url: packages/bigeye-packages.yml
- type: CLI
url: cli/bigeye-cli.yml
- type: ToolCrosswalk
url: mcp/bigeye-tool-crosswalk.yml
- type: Conventions
url: conventions/bigeye-conventions.yml
- type: ErrorCatalog
url: errors/bigeye-problem-types.yml
- type: Lifecycle
url: lifecycle/bigeye-lifecycle.yml
- type: Conformance
url: conformance/bigeye-conformance.yml
- type: DataModel
url: data-model/bigeye-data-model.yml
- type: Webhooks
url: asyncapi/bigeye-webhooks.yml
- type: AgentSkill
url: skills/_index.yml
- type: Security
url: https://www.bigeye.com/platform/security
- type: Overlay
url: overlays/bigeye-metadata-overlay.yaml
- type: ChangeLog
url: changelog/bigeye-changelog.yml
x-enrichment:
date: '2026-08-02'
status: enriched
artifacts_added: 33
pass: local-v1
ⓘWhere this information came from
This is an independent, third-party profile of Bigeye, published by
API Evangelist. We do not operate, host, resell, or
support these APIs, and we are not affiliated with or endorsed by the company unless stated above.
Everything here is built from publicly available information — the company's own site,
developer portal, documentation, public repositories, and the specifications it publishes for public use.
Nothing is obtained by breaching a system, defeating an access control, or using credentials.
The Kin Score and Agent Readiness rating are independently calculated assessments of a company's
public API artifacts, scored against a published rubric. They are not certifications,
endorsements, security assessments, or audits.
Corrections, re-scores, and removal are free — no partnership or purchase required, and
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