The DAMM MCP server brings 4-pillar decision analysis straight into your AI assistant. Ask about a decision and get scores, a Health Score and a structured verdict — without leaving the chat.
One standard, one command. Paste the config into your MCP client.
Add the block to your claude_desktop_config.json and restart Claude.
A single command from the terminal:
claude mcp add damm -- npx -y damm-decision-engine
Google Antigravity, Cursor, Windsurf and any MCP client use the same JSON config block.
{
"mcpServers": {
"damm": {
"command": "npx",
"args": ["-y", "damm-decision-engine"],
"env": { "DAMM_API_KEY": "damm_sk_..." }
}
}
}The env block is optional: omit DAMM_API_KEY for free mode. With the key, analysis runs on the DAMM AI engine.
Prefer self-hosting? Build the package (npm install && npm run build) and use "command": "node" with the absolute path to dist/index.js.
The Model Context Protocol (MCP) is an open standard that lets AI assistants use external tools. An MCP server exposes a capability — here, DAMM decision analysis — to any compatible client, such as Claude or Google Antigravity.
Yes. Being a standard, the same server runs on Claude Desktop, Claude Code, Google Antigravity, Cursor, Windsurf and any MCP client. Only where you paste the config differs.
Not for free mode: the server provides the DAMM method and lets your assistant apply it. Pro mode — which uses the DAMM AI engine, saves decisions and records them in the audit trail — requires an API key with an active plan.
In free mode your assistant runs the analysis following the DAMM structure (4 pillars, Health Score). In pro mode the request goes to the DAMM decision engine, which returns a scored verdict, an EU AI Act (Art. 50) disclosure and an immutable entry in the AI decision registry.
Free to start. Move to the AI engine and audit trail with an API key.
Claude, Claude Code and Google Antigravity are products of their respective owners; the DAMM MCP server is an independent client that integrates via the Model Context Protocol. Pro-mode verdicts are generated by an AI system: human oversight is recommended before acting.