Tecton
Tecton is the enterprise feature platform (feature store) for real-time machine learning and AI at scale. It transforms raw batch, streaming, and real-time data into ML-ready features and embeddings, orchestrates the pipelines that materialize them, and serves them to models online with low latency and ~100ms freshness while guaranteeing training/serving consistency. Developers define features as code with the Python SDK and `tecton` CLI, then read them for inference through the FeatureService HTTP API and open-source Python and Java client libraries. Backed by Andreessen Horowitz, Lux Capital, and SV Angel.
Tecton publishes 1 API on the APIs.io network. Tagged areas include Company, Machine Learning, Feature Store, Feature Platform, and MLOps.
Tecton’s developer surface includes documentation, API reference, getting-started guide, authentication, CLI, and 16 more developer resources.
Kin Score
APIs 1
Individual APIs this provider publishes, each with its own machine-readable definition.
Tecton FeatureService HTTP API
Low-latency online feature serving for model inference — read single or batched feature vectors, wildcard queries, and feature-service metadata. Authenticated with an Authorizat...
MCP Servers 1
Model Context Protocol servers that expose these APIs to AI agents.
tecton-mcp.yml
MCP SERVERSecurity Posture 3
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Resources
Get Started 2
Portal, sign-up, and the first successful call
Documentation 2
Reference material describing how the API behaves
Agent Surfaces 2
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 4
Pagination, idempotency, versioning, errors, and events
Build 4
SDKs, sample code, and the tooling you integrate with
Access & Security 4
Authentication, authorization, and security posture
Operate 2
Status, limits, changes, and where to get help
Company 1
The organization behind the API