---
title: "Tecton"
description: "MCP server for Tecton feature store management, enabling workspace operations and configuration handling for ML teams."
category: "mcp-servers"
tags: ["deployment", "server", "data", "integration", "automation", "feature store", "ML pipeline", "feature governance"]
tech_stack: ["Tecton", "Feature Store", "Machine Learning", "Data Engineering", "MLOps", "API"]
---

This MCP server connects smoothly with Tecton feature stores, giving data scientists and engineers a way to manage their feature infrastructure programmatically.

It helps with workspace discovery, retrieves feature store configurations, and handles operational management through a standard interface. This setup makes developing machine learning pipelines easier by providing reliable access to feature definitions, metadata, and deployment settings.

With this MCP, teams can automate their feature store operations, synchronize feature definitions across different environments, and keep feature governance consistent.

The server also supports essential workflows like feature validation, version tracking, and managing environment-specific configurations. This approach cuts down on manual work and ensures that machine learning projects remain reproducible.