ateam-mcp
Allows building, validating, and deploying multi-agent systems through ChatGPT using the ADAS platform.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@ateam-mcpBuild a customer support system with order tracking and escalation"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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 healthNo context switching. No manual steps. The full ADAS platform — specs, validation, deployment, monitoring — is available as natural language.
Related MCP server: Onboarded MCP Server
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:
{
"mcpServers": {
"ateam": {
"command": "npx",
"args": ["-y", "@ateam-ai/mcp"],
"env": {
"ADAS_TENANT": "your-tenant",
"ADAS_API_KEY": "your-api-key"
}
}
}
}Claude Code — one command:
claude mcp add ateam -- npx -y @ateam-ai/mcpCursor / Windsurf / VS Code (Copilot)
Add to .cursor/mcp.json, mcp_config.json, or .vscode/mcp.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) works with any client that supports Streamable HTTP transport.
Discovery
Developers find ateam-mcp through:
npm —
npm search mcp ai-agents→@ateam-ai/mcpOfficial MCP Registry — registry.modelcontextprotocol.io
Claude Desktop Extensions — built-in extension browser
Claude Code Plugin Marketplace —
/plugin→ Discover tabWindsurf 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 |
| Read the ADAS specification — skill schema, solution architecture, enums, agent guides |
| Get complete working examples — skills, connectors, solutions |
| Validate a skill definition through the 5-stage pipeline |
| Validate a solution — cross-skill contracts + quality scoring |
| Deploy a complete solution to production |
| Add a skill to an existing solution |
| Deploy a connector to ADAS Core |
| List all deployed solutions |
| Inspect a solution — definition, skills, health, status, export |
| Update a solution or skill incrementally (PATCH) |
| Push changes live — regenerates MCP servers, deploys to ADAS Core |
| Talk to the Solution Bot for guided modifications |
Setup
# 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 startArchitecture
┌─────────────────────────────────────────────┐
│ 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
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Servers
AlicenseBqualityDmaintenanceConnects AI assistants (Claude, Cursor, etc.) directly to the HiveFlow automation platform, allowing them to create, manage, and execute automation flows through natural language commands.9164MIT- Flicense-qualityDmaintenanceEnables AI assistants to interact with the Onboarded platform through automatic API discovery and execution, with entity memory persistence and optional source code access from local repositories.
- Alicense-qualityDmaintenanceConnects AI assistants to Supabase projects, enabling them to manage tables, query data, deploy Edge Functions, handle migrations, and access project resources through natural language commands.Apache 2.0
- Alicense-qualityDmaintenanceConnects AI assistants to over 30 business tools like Gmail, Slack, and Airtable through a single unified interface. It enables users to perform actions across multiple platforms using natural language without managing individual API integrations.12MIT
Related MCP Connectors
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
Connect AI assistants to Stellary projects, boards, documents, and governed agent workflows.
Create and manage AI agents that collaborate and solve problems through natural language interacti…
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/ariekogan/ateam-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server