@ateam-ai/mcp

中文文档
0.4.123发布于 2026/11/07MITES Module近 30 天下载 1991

A-Team MCP Server — build, validate, and deploy multi-agent solutions from any AI environment

原始使用文档
文档目录11 节
  1. Why this matters
  2. How it reaches the AI community
  3. ChatGPT users
  4. Claude users
  5. Cursor / Windsurf / VS Code (Copilot)
  6. Gemini and other platforms
  7. Discovery
  8. Available tools
  9. Setup
  10. Architecture
  11. License

ateam-mcp

Give any AI the ability to build, validate, and deploy production multi-agent systems.

This is an MCP server that connects AI assistants — ChatGPT, Claude, Gemini, Copilot, Cursor, Windsurf, and any MCP-compatible environment — directly to the ADAS platform.

An AI developer says "Build me a customer support system with order tracking and escalation" — and their AI assistant handles the entire lifecycle: reads the spec, builds skill definitions, validates them, deploys to production, and verifies health. No manual JSON authoring, no docs reading, no copy-paste workflows.

Why this matters

Today, building multi-agent systems requires deep platform knowledge, manual configuration, and switching between docs, editors, and dashboards. ateam-mcp eliminates all of that by making the ADAS platform a native capability of the AI tools developers already use.

The AI assistant becomes the developer interface:

Developer: "Create an identity verification agent that checks documents,
            validates faces, and escalates fraud cases"

AI Assistant:
  → reads ADAS spec (adas_get_spec)
  → studies working examples (adas_get_examples)
  → builds skill + solution definitions
  → validates iteratively (adas_validate_skill, adas_validate_solution)
  → deploys to production (adas_deploy_solution)
  → verifies everything is running (adas_get_solution → health)

Developer: "Add a new skill that handles address verification"

AI Assistant:
  → deploys into the existing solution (adas_deploy_skill)
  → redeploys (adas_redeploy)
  → confirms health

No context switching. No manual steps. The full ADAS platform — specs, validation, deployment, monitoring — is available as natural language.

How it reaches the AI community

ChatGPT users

ChatGPT supports MCP connectors in Developer Mode. Users connect by pasting a single URL:

Settings → Connectors → Developer Mode → paste https://mcp.ateam-ai.com

That's it. All 12 ADAS tools appear in ChatGPT. Any ChatGPT Pro, Plus, Business, or Enterprise user can build and deploy multi-agent solutions through conversation.

Claude users

claude.ai and Claude Desktop — add the hosted connector: open Customize > Connectors (Claude Desktop: Customize in the sidebar, then Connectors), click Add custom connector, enter https://mcp.ateam-ai.com, and click Connect. The A-Team sign-in page opens in the browser and asks for your workspace's key: copy it from app.ateam-ai.com/connect (a workspace owner or admin) and paste it there. The key decides the workspace; to switch, Disconnect and Connect again with the other workspace's key.

Claude Code — the hosted connector, signed in the same way:

claude mcp add --transport http ateam https://mcp.ateam-ai.com

then /mcp and authenticate in the browser.

Never paste a key into a chat. ateam_bootstrap's session field says which workspace a session is on and how to switch.

Cursor / Windsurf / VS Code (Copilot)

Add the hosted server to .cursor/mcp.json, mcp_config.json, or .vscode/mcp.json:

{
  "mcpServers": {
    "ateam": { "url": "https://mcp.ateam-ai.com/mcp" }
  }
}

A client with OAuth opens the A-Team sign-in page; one without sends the key as Authorization: Bearer <key> from its own config (see below). A local process (npx -y @ateam-ai/mcp) signs in only through ateam_auth: an ADAS_API_KEY in its environment does not sign it in.

Gemini and other platforms

As MCP adoption grows (it's now governed by the Agentic AI Foundation under the Linux Foundation, co-founded by Anthropic, OpenAI, and Block), every AI platform that implements MCP gets access to ateam-mcp automatically. The remote HTTP endpoint (https://mcp.ateam-ai.com, also at /mcp) works with any client that supports Streamable HTTP transport.

The HTTP endpoint needs a credential on every request: OAuth (clients that support it follow the 401 challenge on their own), or your A-Team API key sent as Authorization: Bearer <key>. An anonymous request is refused with 401; since 0.4.93 there is no anonymous session to call ateam_auth from. See CHANGELOG.md.

Discovery

Developers find ateam-mcp through:

  • npm — npm search mcp ai-agents → @ateam-ai/mcp
  • Official MCP Registry — registry.modelcontextprotocol.io
  • Claude Desktop Extensions — built-in extension browser
  • Claude Code Plugin Marketplace — /plugin → Discover tab
  • Windsurf MCP Marketplace — built-in marketplace
  • VS Code MCP Gallery — Extensions view
  • Community directories — Smithery, mcp.so, PulseMCP (30,000+ combined listings)

Available tools

ToolWhat it does
adas_get_specRead the ADAS specification — skill schema, solution architecture, enums, agent guides
adas_get_examplesGet complete working examples — skills, connectors, solutions
adas_validate_skillValidate a skill definition through the 5-stage pipeline
adas_validate_solutionValidate a solution — cross-skill contracts + quality scoring
adas_deploy_solutionDeploy a complete solution to production
adas_deploy_skillAdd a skill to an existing solution
adas_deploy_connectorDeploy a connector to ADAS Core
adas_list_solutionsList all deployed solutions
adas_get_solutionInspect a solution — definition, skills, health, status, export
adas_updateUpdate a solution or skill incrementally (PATCH)
adas_redeployPush changes live — regenerates MCP servers, deploys to ADAS Core
adas_solution_chatTalk to the Solution Bot for guided modifications
ateam_workspace_openFor a chat agent with no shell: open one private workspace (files in /workspace) for the conversation
ateam_workspace_execRun one command in the workspace (100 s foreground; run_in_background for long builds)
ateam_workspace_statusCheck the workspace: unsaved changes, a long save or background command
ateam_workspace_saveMake the workspace's work live (the only way the other tools see it)
ateam_workspace_closeFinish; optionally save first. Brings back the single-file write tools withheld while it was open

The ateam_workspace_* tools are listed whenever you are signed in. A workspace the platform cannot give (a trial workspace, a key tied to no person) is refused by the call itself, with the single-file tools to use instead.

Setup

# Clone
git clone https://github.com/ariekogan/ateam-mcp.git
cd ateam-mcp

# Install
npm install

# Run (a local stdio process)
npm start

A local process signs in with ateam_auth, given a workspace key the agent reads from a file outside the chat; an ADAS_API_KEY in the environment does not sign it in and is never sent. ADAS_API_URL in its environment points it at a self-hosted API. Most people use the hosted connector instead (above).

Architecture

┌─────────────────────────────────────────────┐
│  AI Environment                             │
│  (ChatGPT / Claude / Cursor / Windsurf)     │
│                                             │
│  Developer: "build me a support system"     │
└──────────────────┬──────────────────────────┘
                   │ MCP protocol
                   │ (stdio or HTTP)
┌──────────────────▼──────────────────────────┐
│  ateam-mcp                                  │
│  12 tools — spec, validate, deploy, manage  │
└──────────────────┬──────────────────────────┘
                   │ HTTPS
                   │ X-ADAS-TENANT / X-API-KEY
┌──────────────────▼──────────────────────────┐
│  ADAS External Agent API                    │
│  api.ateam-ai.com                           │
└──────────────────┬──────────────────────────┘
                   │
┌──────────────────▼──────────────────────────┐
│  ADAS Core                                  │
│  Multi-agent runtime                        │
└─────────────────────────────────────────────┘

License

MIT

版本与发布记录

@ateam-ai/mcp 共发布 201 个版本,首次发布于 2026/02/18;过去 12 个月发布了 201 个版本。

版本发布日期距今
0.4.123latest2026/11/07今天
0.4.1222026/11/061 天前
0.4.1212026/11/061 天前
0.4.1202026/10/2810 天前
0.4.1192026/10/1424 天前
0.4.1182026/10/1325 天前

关于 @ateam-ai/mcp 的常见问题

@ateam-ai/mcp 是什么?

A-Team MCP Server — build, validate, and deploy multi-agent solutions from any AI environment

如何安装 @ateam-ai/mcp?

在项目目录运行 npm install @ateam-ai/mcp,或使用 pnpm add / yarn add / bun add。它还提供命令行工具 ateam-mcp,可以用 npx ateam-mcp 直接运行。

@ateam-ai/mcp 支持 TypeScript 吗?

该包的 package.json 没有声明类型入口。需要类型提示时,可以在 npm 上查找社区维护的 @types/ateam-ai__mcp 是否存在。

@ateam-ai/mcp 支持 ESM 还是 CommonJS?

以 ES Module 形式发布,推荐使用 import 引入。在 CommonJS 项目中,Node.js 20.19+ / 22.12+ 可以直接 require() 不含顶层 await 的 ES Module,更早的版本需要改用动态 import()。

@ateam-ai/mcp 需要什么版本的 Node.js?

package.json 的 engines 字段要求 Node.js >=18.0.0。版本不符时 npm 默认只给出警告,开启 engine-strict 后会拒绝安装。

@ateam-ai/mcp 可以商用吗?

@ateam-ai/mcp 使用 MIT 许可。宽松许可:允许商业使用、修改和再分发,通常只需在分发时保留原版权与许可声明。以上为概括,不构成法律意见,请以许可原文为准。

@ateam-ai/mcp 的下载量有多少?

根据 npm 官方下载统计,@ateam-ai/mcp 在 2026/10/07 – 2026/11/05 这 30 天内被下载 1,991 次,日均约 66 次。下载量会把 CI 构建、镜像同步和作为其他包依赖的安装一并计入,适合横向比较热度,不能直接等同于使用人数。

@ateam-ai/mcp 还在维护吗?

最新版本 0.4.123 发布于 2026/11/07(今天);至今共发布 201 个版本,其中过去 12 个月发布了 201 个;首次发布于 2026/02/18。发布频率只是参考信号:功能稳定的工具可能很少需要更新,建议结合源码仓库的 issue 和提交记录判断。