Software Engineering

AI-assisted TeamCity troubleshooting, onboarding, and build inspection

Use AI with TeamCity CLI, MCP, and in-product assistance to inspect builds, analyze failures, explain project and build context, surface relevant documentation, and speed up onboarding and CI troubleshooting from both the UI and external AI tools.

Why the human is still essential here

Developers and DevOps teams still decide which failures matter, interpret the guidance, choose the right configuration or recovery actions, and remain responsible for final build, project, and operational decisions.

How people use this

Build log root-cause summaries

AI reads TeamCity build logs, test output, and recent changes to produce a likely root-cause summary and highlight the failing step for engineer review.

Claude / ChatGPT

Terminal CI investigation agent

An engineer uses a coding agent from the terminal to query TeamCity through MCP or CLI, pull failed job details, and explain what changed between green and broken runs.

Claude Code / TeamCity MCP

Suggested reruns and recovery actions

AI analyzes failure patterns to recommend rerunning flaky tests, starting a remote build with safer parameters, or checking a specific dependency before a human approves the action.

ChatGPT / TeamCity CLI

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News
Blog

TeamCity 2026.1: CLI, MCP for AI Agents, Pipelines Enhancements, and More

TL;DR: TeamCity 2026.1 is out and packed with helpful features. We’re introducing the TeamCity CLI and MCP support, as well as Pipelines enhancements to make configuring TeamCity more convenient and powerful. As of this release, AI Assistant is available in Enterprise trial accounts, and the SAML authentication plugin comes bundled with TeamCity.

OB
Olga BedrinaContent Writer on the TeamCity and Strategic Research and Market Intelligence teams at JetBrains
May 12, 2026