原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Teamcity

作者:Daghis版本 2.12.15i★ –i在你的电脑上运行
注册名称io.github.Daghis/teamcity

安装

概览

作者提供的说明(英文原文)

MCP server exposing JetBrains TeamCity CI/CD workflows to AI coding assistants

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 开发者工具
  • 你需要填写:TEAMCITY_URL, TEAMCITY_TOKEN

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: TEAMCITY_URL, TEAMCITY_TOKEN, MCP_MODE

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "teamcity": {
      "command": "npx",
      "args": [
        "-y",
        "@daghis/teamcity-mcp"
      ],
      "env": {
        "TEAMCITY_URL": "your-value",
        "TEAMCITY_TOKEN": "your-value",
        "MCP_MODE": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add teamcity --env TEAMCITY_URL=your-value --env TEAMCITY_TOKEN=your-value --env MCP_MODE=your-value -- npx -y @daghis/teamcity-mcp

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "teamcity": {
      "command": "npx",
      "args": [
        "-y",
        "@daghis/teamcity-mcp"
      ],
      "env": {
        "TEAMCITY_URL": "your-value",
        "TEAMCITY_TOKEN": "your-value",
        "MCP_MODE": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "teamcity": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@daghis/teamcity-mcp"
      ],
      "env": {
        "TEAMCITY_URL": "your-value",
        "TEAMCITY_TOKEN": "your-value",
        "MCP_MODE": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • TEAMCITY_URL 必填 env
    Base URL of your TeamCity server
  • TEAMCITY_TOKEN 机密 必填 env
    TeamCity personal access token with required permissions
  • MCP_MODE env
    Operational mode: dev (default) or full for elevated administrative tools

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 Daghis 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“开发者工具”中的其他服务器比较i

  • 星标数多于此分类中其他 1396 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 1396 个服务器的 99% 更新
  • 基础检查结果等于或优于此分类中其他 1396 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Teamcity 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

你需要填写:TEAMCITY_URL, TEAMCITY_TOKEN

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(2.12.15)于今天进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。

有什么可以替代它?

同一分类中有:GitHub, Desktop Commander, Cloudflare MCP

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

GitHub

作者:github

Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.

电脑或云端★ 34,245MIT4天前更新
安装

Desktop Commander

作者:wonderwhy-er

MCP server for terminal commands, file operations, and process management

在你的电脑上运行★ 10,225MIT16天前更新
安装

Cloudflare MCP

作者:cloudflare

Cloudflare MCP servers

在云端运行★ 4,446Apache-2.014个月前更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

TeamCity MCP Server

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 (October 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 — an MCP server built into TeamCity 2026.1+ 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 October 2026 (TeamCity 2026.2, TeamCity CLI 1.6), JetBrains ships two first-party paths for AI agents, both generally available and officially supported:

  • Built-in MCP server — every TeamCity 2026.1+ server (Cloud and On-Premises) exposes an MCP endpoint at /app/mcp, so there's nothing to install. It's a deliberately small toolset: build logs, generic REST API GET/POST passthrough tools, and (since 2026.2) pipeline tools. By default it runs in a safe mode where the agent can read and queue personal builds; an opt-in "brave mode" lets it send arbitrary REST POST requests and edit or delete pipelines. Since 2026.2 you can also sign in with OAuth instead of pasting an access token.
  • [TeamCity CLI](https://github.com/JetBrains/teamcity-cli) — an open-source teamcity command (TeamCity 2020.1+) with an installable agent skill (teamcity skill install) for Claude Code, Cursor, and other agents. It covers runs, logs, tests, the queue, agents, pools, projects, VCS roots, parameters, and pipelines, falls back to raw REST access via teamcity api, and has a read-only mode (TEAMCITY_RO=1). JetBrains' own docs describe it as the broader of the two options.

teamcity-mcp predates that tooling and overlaps with it heavily. The official tooling is the better default today. What teamcity-mcp still offers is narrower than it used to be:

  • An MCP server for servers older than 2026.1. If your client speaks only MCP and your TeamCity server predates the built-in endpoint, this still works (TeamCity 2020.1+).
  • Purpose-built MCP tools instead of a REST passthrough. It exposes 87 typed tools (gated by Dev/Full mode), so the agent doesn't need to know REST paths and locators — and it covers operations backed by PUT/DELETE (such as enabling agents or deleting parameters), which the built-in MCP's generic GET/POST tools don't reach.

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:

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
  • Node.js >= 20.10.0 (LTS versions 20, 22, 24 tested in CI)
  • TeamCity Server 2020.1+ with REST API access
  • TeamCity authentication token
Quick Start
# Clone the repository

git clone https://github.com/Daghis/teamcity-mcp.git cd teamcity-mcp

Install dependencies

npm install

Configure environment

cp .env.example .env

Edit .env with your TeamCity URL and token

Run in development mode

npm run dev

npm Package

Run the MCP server via npx (requires Node 20.x). Set your TeamCity environment variables inline or via a .env in the working directory.

# One-off run (inline envs)

TEAMCITY_URL="https://teamcity.example.com" \ TEAMCITY_TOKEN=" " \ MCP_MODE=dev \ npx -y @daghis/teamcity-mcp

Or rely on .env in the current directory

npx -y @daghis/teamcity-mcp

Claude Code

  • Add the MCP (relying on .env for configuration):
  • claude mcp add teamcity -- npx -y @daghis/teamcity-mcp
  • With env vars (if not using .env):
  • claude mcp add teamcity -e TEAMCITY_URL="https://teamcity.example.com" -e TEAMCITY_TOKEN="tc_ " -- npx -y @daghis/teamcity-mcp
  • With CLI arguments (recommended for Windows):
  • claude mcp add teamcity -- npx -y @daghis/teamcity-mcp --url "https://teamcity.example.com" --token "tc_ " --mode dev
  • Add -s user to install user-wide instead of project-scoped (default)
  • Context usage (Opus 4.1, estimates):
  • Dev (default): ~14k tokens for MCP tools
  • Full (MCP_MODE=full): ~26k tokens for MCP tools
Windows Users

On Windows, Claude Code's MCP configuration may not properly merge environment variables. Use CLI arguments as a workaround:

{

"mcpServers": { "teamcity": { "command": "npx", "args": [ "-y", "@daghis/teamcity-mcp", "--url", "https://teamcity.example.com", "--token", "YOUR_TOKEN" ] } } }

Or use a config file for better security (token not visible in process list):

{

"mcpServers": { "teamcity": { "command": "npx", "args": ["-y", "@daghis/teamcity-mcp", "--config", "C:\\path\\to\\teamcity.env"] } } }

Configuration

Environment is validated centrally with Zod. Supported variables and defaults:

# Server Configuration

PORT=3000 NODE_ENV=development LOG_LEVEL=info

TeamCity Configuration (aliases supported)

TEAMCITY_URL=https://teamcity.example.com TEAMCITY_TOKEN=your-auth-token

Optional aliases:

TEAMCITY_SERVER_URL=...

TEAMCITY_API_TOKEN=...

MCP Mode (dev or full)

MCP_MODE=dev

Optional advanced TeamCity options (defaults shown)

Connection

TEAMCITY_TIMEOUT=30000

TEAMCITY_MAX_CONCURRENT=10

TEAMCITY_KEEP_ALIVE=true

TEAMCITY_COMPRESSION=true

Extra headers attached to every TeamCity request — useful when TeamCity

sits behind a reverse proxy that gates access on custom headers (e.g.

Cloudflare Zero Trust service tokens). One env var per header; the part

after TEAMCITY_HEADER_ is used verbatim as the HTTP header name.

Example (note the literal hyphens — most shells need quoting):

TEAMCITY_HEADER_CF-Access-Client-Id=

TEAMCITY_HEADER_CF-Access-Client-Secret=

Retry

TEAMCITY_RETRY_ENABLED=true

TEAMCITY_MAX_RETRIES=3

TEAMCITY_RETRY_DELAY=1000

TEAMCITY_MAX_RETRY_DELAY=30000

Pagination

TEAMCITY_PAGE_SIZE=100

TEAMCITY_MAX_PAGE_SIZE=1000

TEAMCITY_AUTO_FETCH_ALL=false

Circuit Breaker

TEAMCITY_CIRCUIT_BREAKER=true

TEAMCITY_CB_FAILURE_THRESHOLD=5

TEAMCITY_CB_RESET_TIMEOUT=60000

TEAMCITY_CB_SUCCESS_THRESHOLD=2

These values are normalized in src/config/index.ts and consumed by src/teamcity/config.ts via helper getters.

Usage Examples

Once integrated with your AI coding assistant:

"Build the frontend on feature branch"

"Why did last night's tests fail?" "Deploy staging with the latest build" "Create a new build config for the mobile app"

Tool Responses and Pagination
  • Responses: Tools now return consistent MCP content. For list/get operations, the content[0].text contains a JSON string. Example shape: { "items": [...], "pagination": { "page": 1, "pageSize": 100 } } or { "items": [...], "pagination": { "mode": "all", "pageSize": 100, "fetched": 250 } }.
  • Pagination: Most list\_\* tools accept pageSize, maxPages, and all:
  • pageSize controls items per page.
  • all: true fetches multiple pages up to maxPages.
  • Legacy count on list_builds is kept for compatibility but pageSize is preferred.
Validation and Errors
  • Input validation: Tool inputs are validated with Zod schemas; invalid input returns a structured error payload in the response content (JSON string) with success: false and error.code = VALIDATION_ERROR.
  • Error shaping: Errors are formatted consistently via a global handler. In production, messages may be sanitized; sensitive values (e.g., tokens) are redacted in logs.
API Usage
import { TeamCityAPI } from '@/api-client';

// Get the API client instance const api = TeamCityAPI.getInstance();

// List projects const projects = await api.listProjects();

// Get build status const build = await api.getBuild('BuildId123');

// Trigger a new build const newBuild = await api.triggerBuild('BuildConfigId', { branchName: 'main', });

Note: The legacy helpers exported from src/teamcity/index.ts remain only for compatibility and include placeholder impl

只显示了开头部分;其余内容请在仓库中阅读

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