Tecton (Databricks)

Tecton is a feature platform (feature store) for machine learning and AI. It lets data and ML teams define feature transformations once and run them across batch, streaming, and real-time data sources, then materialize and serve those features from a low-latency online store. Features are authored in Python and managed GitOps-style via the tecton CLI and SDK, and consumed at inference time over the Feature Service HTTP API (Authorization: Tecton-key, or Service-Account OAuth). Tecton also ships an Ingest API, a Metadata API, an official MCP server, and Java/Python clients. The company was acquired by Databricks in August 2025 and its platform now powers real-time features and context serving for AI agents.

Tecton (Databricks) publishes 1 API on the APIs.io network. Tagged areas include Company, Ai Infrastructure, Feature Store, Feature Platform, and Machine Learning.

Tecton (Databricks)’s developer surface includes documentation, API reference, getting-started guide, engineering blog, support, changelog, CLI, and 18 more developer resources.

🌐 Visit website 📡 Source on GitHub

34.1/100 thin ▬ flat Agent 29/100 agent aware Full breakdown ↓
scored 2026-07-27 · rubric v0.5

AccessSelf serve

1 APIs 1 MCP Servers

CompanyAi InfrastructureFeature StoreFeature PlatformMachine LearningMLOpsReal TimeDatabricks

Kin Score

Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5

Composite quality — 34.1/100 · thin

Contract Quality 0.0 / 25

Developer Ergonomics 14.8 / 20

Commercial Clarity 7.4 / 20

Operational Transparency 2.7 / 13

Governance 0.0 / 12

Discoverability 9.3 / 10

Agent readiness — 29/100 · agent aware

Machine-Readable Contract 0 / 18

Agentic Access Contract 0 / 15

MCP Server 12 / 12

Machine-Readable Auth 10 / 10

Idempotency 0 / 9

Stable Error Semantics 8 / 8

Request/Response Examples 0 / 7

Rate-Limit Signaling 0 / 7

Typed Event Surface 0 / 6

Agent Skills 0 / 5

Well-Known Catalog 0 / 4

Consent & Bot Identity 0 / 3

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/tecton-databricks: 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.

Tecton HTTP API

REST API for the Tecton feature platform - the Feature Service (low-latency online feature retrieval, e.g. POST /api/v1/feature-service/get-features), the Ingest API, the Metada...

MCP Servers 1

Model Context Protocol servers that expose these APIs to AI agents.

Get Started 2

Portal, sign-up, and the first successful call

DeveloperPortal

DeveloperPortal

GettingStarted

GettingStarted

Documentation 2

Reference material describing how the API behaves

Documentation

Documentation

APIReference

APIReference

Agent Surfaces 2

MCP servers, agent skills, and machine-readable catalogs

MCPServer

MCPServer

LLMsTxt

LLMsTxt

Design & Contract 4

Pagination, idempotency, versioning, errors, and events

Conventions

ErrorCatalog

Lifecycle

Conformance

Build 4

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

Packages

SDKs

CLI

Access & Security 4

Authentication, authorization, and security posture

Compliance

Authentication

TrustCenter

DomainSecurity

Operate 3

Status, limits, changes, and where to get help

Support

Support

ChangeLog

ChangeLog

ChangeLog

ChangeLog

Commercial 2

Pricing, plans, and the legal terms of use

TermsOfService

TermsOfService

PrivacyPolicy

PrivacyPolicy

Company 2

The organization behind the API

Website

Website

Blog

Blog

Source (apis.yml)

aid: tecton-databricks
accessModel:
  pricing: unknown
  onboarding: self-serve
  trial: false
  try_now: false
  public: false
  label: Self-serve signup
  confidence: medium
  source:
  - authentication
  generated: '2026-07-22'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/tecton-databricks.png
name: Tecton (Databricks)
description: 'Tecton is a feature platform (feature store) for machine learning and AI. It lets data and ML teams define feature
  transformations once and run them across batch, streaming, and real-time data sources, then materialize and serve those
  features from a low-latency online store. Features are authored in Python and managed GitOps-style via the tecton CLI and
  SDK, and consumed at inference time over the Feature Service HTTP API (Authorization: Tecton-key, or Service-Account OAuth).
  Tecton also ships an Ingest API, a Metadata API, an official MCP server, and Java/Python clients. The company was acquired
  by Databricks in August 2025 and its platform now powers real-time features and context serving for AI agents.'
url: https://raw.githubusercontent.com/api-evangelist/tecton-databricks/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- bain-capital-ventures
x-tier: stub
x-tier-reason: portfolio-lead
specificationVersion: '0.20'
created: '2026-07-17'
modified: '2026-07-21'
tags:
- Company
- Ai Infrastructure
- Feature Store
- Feature Platform
- Machine Learning
- MLOps
- Real Time
- Databricks
apis:
- name: Tecton HTTP API
  description: REST API for the Tecton feature platform - the Feature Service (low-latency online feature retrieval, e.g.
    POST /api/v1/feature-service/get-features), the Ingest API, the Metadata API, and SCIM 2.0 provisioning. Authenticated
    with an Authorization Tecton-key header or a Service-Account OAuth access token. The runtime host is per-deployment (https://<deployment>.tecton.ai);
    see the HTTP API reference.
  humanURL: https://docs.tecton.ai/http-api
  baseURL: https://docs.tecton.ai
  properties:
  - type: APIReference
    url: https://docs.tecton.ai/http-api
  - type: Authentication
    url: authentication/tecton-databricks-authentication.yml
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Website
  url: https://www.tecton.ai/
- type: DeveloperPortal
  url: https://docs.tecton.ai/
- type: Documentation
  url: https://docs.tecton.ai/
- type: APIReference
  url: https://docs.tecton.ai/http-api
- type: GettingStarted
  url: https://docs.tecton.ai/docs/tutorials/tecton-quick-start
- type: Blog
  url: https://www.tecton.ai/blog/
- type: GitHubOrganization
  url: https://github.com/tecton-ai
- type: Support
  url: https://support.tecton.ai/
- type: TermsOfService
  url: https://www.tecton.ai/terms-of-use/
- type: PrivacyPolicy
  url: https://www.tecton.ai/privacy-policy/
- type: ChangeLog
  url: https://www.tecton.ai/whats-new/
- type: Compliance
  url: https://docs.tecton.ai/docs/security
- type: Packages
  url: packages/tecton-databricks-packages.yml
- type: SDKs
  url: packages/tecton-databricks-packages.yml
- type: CLI
  url: cli/tecton-databricks-cli.yml
- type: MCPServer
  url: mcp/tecton-databricks-mcp.yml
- type: LLMsTxt
  url: llms/tecton-databricks-llms.txt
- type: Authentication
  url: authentication/tecton-databricks-authentication.yml
- type: Conventions
  url: conventions/tecton-databricks-conventions.yml
- type: ErrorCatalog
  url: errors/tecton-databricks-problem-types.yml
- type: Lifecycle
  url: lifecycle/tecton-databricks-lifecycle.yml
- type: ChangeLog
  url: changelog/tecton-databricks-changelog.yml
- type: Conformance
  url: conformance/tecton-databricks-conformance.yml
- type: TrustCenter
  url: security/tecton-databricks-trust-center.yml
- type: DomainSecurity
  url: security/tecton-databricks-domain-security.yml
x-enrichment:
  date: '2026-07-21'
  status: enriched
  artifacts_added: 13
  pass: local-v1