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# 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](https://ateam-ai.com) 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 Desktop** — install as an extension (one-click) or add to config:

```json
{
  "mcpServers": {
    "ateam": {
      "command": "npx",
      "args": ["-y", "@ateam-ai/mcp"],
      "env": {
        "ADAS_TENANT": "your-tenant",
        "ADAS_API_KEY": "your-api-key"
      }
    }
  }
}
```

**Claude Code** — one command:

```bash
claude mcp add ateam -- npx -y @ateam-ai/mcp
```

### Cursor / Windsurf / VS Code (Copilot)

Add to `.cursor/mcp.json`, `mcp_config.json`, or `.vscode/mcp.json`:

```json
{
  "mcpServers": {
    "ateam": {
      "command": "npx",
      "args": ["-y", "@ateam-ai/mcp"],
      "env": {
        "ADAS_TENANT": "your-tenant",
        "ADAS_API_KEY": "your-api-key"
      }
    }
  }
}
```

### 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](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

| Tool | What it does |
|---|---|
| `adas_get_spec` | Read the ADAS specification — skill schema, solution architecture, enums, agent guides |
| `adas_get_examples` | Get complete working examples — skills, connectors, solutions |
| `adas_validate_skill` | Validate a skill definition through the 5-stage pipeline |
| `adas_validate_solution` | Validate a solution — cross-skill contracts + quality scoring |
| `adas_deploy_solution` | Deploy a complete solution to production |
| `adas_deploy_skill` | Add a skill to an existing solution |
| `adas_deploy_connector` | Deploy a connector to ADAS Core |
| `adas_list_solutions` | List all deployed solutions |
| `adas_get_solution` | Inspect a solution — definition, skills, health, status, export |
| `adas_update` | Update a solution or skill incrementally (PATCH) |
| `adas_redeploy` | Push changes live — regenerates MCP servers, deploys to ADAS Core |
| `adas_solution_chat` | Talk to the Solution Bot for guided modifications |

## Setup

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

# Install
npm install

# Configure
cp .env.example .env
# Edit .env with your ADAS tenant and API key

# Run
npm start
```

## 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

TDQS

A4/5.0

Scored across 41 tools

Disambiguation5/5

Each tool targets a distinct purpose. Authentication, onboarding, CRUD for connectors/skills/solutions, various GitHub operations (patch, promote, push, pull, rollback), and multiple testing modes (skill, connector, notification, voice, pipeline) are all clearly separated. No two tools perform the same function, and descriptions are detailed enough to differentiate similar operations like ateam_build_and_run vs ateam_redeploy.

Naming Consistency4/5

All tools share the ateam_ prefix and most follow a verb_noun pattern (e.g., ateam_create_connector, ateam_test_skill). However, a few tools use noun-only names (ateam_conversation, ateam_get_examples) or compound verbs (ateam_build_and_run), breaking the pattern slightly. Overall, the naming is largely consistent and predictable.

Tool Count3/5

With 41 tools, the server exceeds the typical range of 3-15 tools for a well-scoped server. However, the domain is broad, covering authentication, CRUD, GitHub integration, testing, and admin operations, which justifies many tools. Some consolidation might be possible, but the count is borderline heavy.

Completeness5/5

The tool surface covers the full lifecycle of solution development: onboarding, authentication, creating/deleting/reading components, comprehensive GitHub operations (diff, log, patch, promote, push, pull, rollback, status), multiple testing modalities (skill, connector, notification, voice, pipeline, abort, status), and admin tools (sync_all, status_all). No obvious gaps are evident.

Maintenance

ActivityActive
ResponsivenessSlow