DEPLOY

For AI assistants

Use DEPLOY in your AI assistant

Connect Claude (or any MCP-aware assistant) to the DEPLOY registry. Ask questions about robot deployments, AI brains, incidents, and regulations and get answers grounded in verified data instead of training memory.

Install for Claude Desktop

Download the extension. Double-click the file to install. Restart Claude.

Download .dxt (5 KB) For Claude Desktop 0.10+

Or paste the URL into any MCP client

If your client supports remote MCP servers (Claude Desktop, Cursor, Claude Code, and most newer MCP clients do), just add this URL in the app's MCP settings:

Step-by-step: Claude Desktop

Recent Claude Desktop versions (2025+) support adding remote MCP servers from the UI:

  1. Open Claude Desktop
  2. Settings → Developer → Edit Config (or use the .dxt download above for one-click)
  3. If using config editor, paste:
    {
      "mcpServers": {
        "deploy-registry": {
          "url": "https://registry.deploy.report/mcp"
        }
      }
    }
  4. Save, restart Claude
  5. You should see "deploy-registry" in the tool list (small icon in the input bar)

On older Claude Desktop versions that don't support remote MCP, use the bridge config below.

Bridge config (works on every version):

{
  "mcpServers": {
    "deploy-registry": {
      "command": "npx",
      "args": ["-y", "mcp-remote@latest", "https://registry.deploy.report/mcp"]
    }
  }
}
Step-by-step: Cursor
  1. Open Cursor
  2. Settings → Features → MCP (or Settings → MCP depending on version)
  3. Click "Add new MCP server"
  4. Name: deploy-registry
  5. If Cursor offers a "URL" type, paste: https://registry.deploy.report/mcp
  6. Otherwise use command type: command npx, args ["-y", "mcp-remote@latest", "https://registry.deploy.report/mcp"]
  7. Save, restart Cursor
Step-by-step: Claude Code, Continue, other MCP clients

Most MCP clients accept either a direct URL or a stdio bridge command. Use:

Refer to your client's MCP documentation for where to enter these.

Try these prompts

Once installed, open a new conversation and try:

Your AI assistant calls the registry tools automatically when relevant. You don't have to invoke them manually.

What's available

The MCP server exposes 5 tools that wrap DEPLOY's verified registry:

search_entities
Search the DEPLOY registry across companies, models, deployments, brains, incidents, regulations, and locations. Returns matching entities with canonical names, registry URLs, and entity types.
get_entity
Get full details for one entity by its canonical UUID. Returns the entity record plus schema.org JSON-LD structured data. Use search_entities first to resolve a name to a UUID.
get_deployments_at_location
List verified robot deployments at a specific location (by location slug). Returns deployment records with model, operator, status, and dates.
get_deployments_for_model
List verified deployments of a specific robot model (by model slug). Returns deployments with location, operator, and dates.
get_recent_incidents
List the most recently recorded incidents. Returns headline, occurredAt, kind, and slug. Useful for surfacing the latest events in the registry.

Why this matters

AI assistants are typically limited to training-set knowledge, which goes stale fast on a domain that's evolving as quickly as physical AI. The DEPLOY registry is live, sourced, and human-reviewed. Connecting your assistant to it means answers about robots, deployments, and incidents reflect what's actually verified in the world, not what the training data caught.

DEPLOY also distinguishes verified deployments from manufacturer claims. When your assistant queries DEPLOY, that distinction surfaces in the response. Read our methodology for the full editorial framework.

Help + troubleshooting

If something doesn't work:

For developers

Direct API access: