Daghis/teamcity-mcp

A Model Control Protocol (MCP) server that bridges AI coding assistants with JetBrains TeamCity CI/CD server, exposing TeamCity operations as MCP tools.
> [!NOTE]
> **Project status (June 2026): stable, low-key maintenance.** This does what it set out to do and is no longer under active development. It still works and stays installable; issues and PRs may get slow or no response, and security fixes are best-effort.
>
> JetBrains now ships official AI integration for TeamCity — a built-in MCP and the TeamCity CLI with an installable agent skill — which is the better default for most workflows. See _How this compares to JetBrains' official tooling_ below before adopting.
Overview
The TeamCity MCP Server allows developers using AI-powered coding assistants (Claude Code, Cursor, Windsurf) to interact with TeamCity directly from their development environment via MCP tools.
> **Upgrading from 1.x?** Version 2.0.0 moved 15 tools from Dev to Full mode, including queue management, agent compatibility checks, and server health monitoring. If you relied on these tools in Dev mode, switch to MCP_MODE=full or use runtime mode switching (v2.1.0+). See CHANGELOG.md for details.
Features
🚀 Two Operational Modes
- **Dev Mode** (default): Safe CI/CD operations (31 tools, ~14k context tokens)
- Trigger builds and monitor status
- Fetch build logs and inspect test failures
- List projects, configurations, and queue
- Read parameters and investigate problems
- **Full Mode**: Complete infrastructure management (87 tools, ~26k context tokens)
- All Dev mode features, plus:
- Create and clone build configurations
- Manage build steps, triggers, and dependencies
- Configure VCS roots and agents
- Full CRUD for parameters (build config, project, and output parameters)
- Queue management and server administration
**Runtime Mode Switching (v2.1.0+):** Switch between modes at runtime using the get_mcp_mode and set_mcp_mode tools—no restart required. MCP clients that support notifications will see the tool list update automatically.
See the Tools Mode Matrix for the complete list of 87 tools and their availability by mode.
🎯 Key Capabilities
- Trigger and monitor builds, fetch logs, and inspect test failures
- Token-based authentication to TeamCity; sensitive values redacted in logs
- Modern architecture: simple, direct implementation with a singleton client
- Performance-conscious: fast startup with minimal overhead
- Clean codebase with clear module boundaries
How this compares to JetBrains' official tooling
**As of June 2026,** JetBrains ships first-party AI integration for TeamCity: a built-in MCP endpoint and the TeamCity CLI, which includes an installable agent skill. Together these are JetBrains' recommended path and cover the common AI workflows — reading logs, diagnosing failures, and rerunning builds — with no install and official support.
teamcity-mcp predates that tooling and overlaps with it. Broadly, the official tooling is the better default today; teamcity-mcp's remaining edge is a broader set of write and management operations exposed as an MCP server. That gap is real but narrowing, and JetBrains' tooling is evolving quickly — so rather than pin down a feature-by-feature comparison here (it would go stale fast), check the current docs and pick what fits:
- TeamCity 2026.1 announcement — overview of the official AI integration
- AI agent integration docs — the built-in MCP
- TeamCity CLI — the terminal + agent-skill path
If you're comfortable with JetBrains' CLI, you may not need this project at all. It stays MIT-licensed and installable for whatever the built-ins don't yet reach — fork it if you want to take it further yourself.
Installation
Prerequisites