Developers
Connect your AI assistant. Describe what to build.
A-Team MCP gives capable coding assistants a governed interface to learn the platform, create solutions, validate, deploy, test, inspect, and iterate.
Public MCP · use any assistant
Build A-Team solutions with the AI you already use.
Connect Claude Code, ChatGPT, Cursor—any MCP assistant—to A-Team. It reads the spec, designs your solution, deploys, and tests while you describe the outcome. No lock-in: every solution is Git-backed and yours to keep.
Setup · 2 steps
- 1
- 2
Copy your workspace key
Paste it into your assistant when it asks—that's the only thing it needs to connect.
adas_<workspace>_<key>
Then just tell your assistant: “Connect to A-Team MCP.”
ChatGPT connects to A-Team as tools and builds a full solution for you.
See it in Claude Code
Add the MCP once, then just describe the outcome. Claude Code connects to A-Team and builds it—reading the spec, deploying, and testing—right in your terminal.
Watch Claude Code connect to A-Team and build a solution from one sentence.
Connect your assistant and start exploring
Point any MCP client at A-Team with no key. It bootstraps, learns the platform, and drafts a working solution with you. When you're ready to validate and deploy, it prompts you to create a free workspace—grab your tenant key from Tokens & Keys in the app and paste it when asked.
https://mcp.ateam-ai.comnpm: @ateam-ai/mcpChatGPT
Developer Mode connectorSettings → Connectors → Developer Mode
Paste: https://mcp.ateam-ai.comClaude Code
one commandclaude mcp add ateam -- npx -y @ateam-ai/mcpClaude Desktop · Cursor · VS Code
mcp.json{
"mcpServers": {
"ateam": {
"command": "npx",
"args": ["-y", "@ateam-ai/mcp"]
}
}
}Works with any MCP-compatible client (Gemini, Copilot, Windsurf, …) over Streamable HTTP or stdio.
Quick start
Five steps to your first system.
- 1Get an A-Team API key.
- 2Add the MCP endpoint to your assistant.
- 3Ask it to bootstrap and inspect examples.
- 4Describe the desired system.
- 5Review, deploy, and test.
$ connect a-team mcp
→ bootstrap · learn the spec
→ inspect examples
→ describe the system
→ review architecture
→ deploy · test · improve
✓ solution deployed
Mental model
Four concepts to hold.
Solution
The complete application topology.
Skill
An operational AI role.
Connector
A controlled MCP integration.
Governance
Permissions, contracts, policies, and handoffs.
Lifecycle
Learn → build → observe → version.
Get an API key
Request access to A-Team MCP and start building with your assistant. Key issuance and client-specific configuration are documented once verified.