MCP Servers
kaleido-mcp is the quickest path to a first tool call, published to npm. KALEIDO_NETWORK=signet points it at the signet KaleidoSwap API and Spark’s test network in one variable:
Directly launching the stdio server waits for an MCP client; it is not a chat prompt.
Add the command to your client’s configuration, then request a tool call.
npx. To enable them, run npx -y -p kaleido-mcp -p @tetherto/wdk-wallet-spark -p @kaleidorg/wdk-wallet-liquid kaleido-mcp and set WDK_SEED / LIQUID_MNEMONIC.
For the RGB tools you also need an RGB Lightning Node. KaleidoCLI runs one on signet in Docker, see Build a Local RGB Agent for the full path.
For the tool catalog and client configuration, see MCP Servers.
The unified server includes the older wallet servers’ domains. Existing users can
follow the migration notes.
KaleidoAgent
Prerequisites: Node.js 20 or newer, KaleidoCLI in$PATH, the Nanobot runtime, and an Anthropic or OpenAI API key.
agent.config.json, start the dashboard, or deploy in a container, check the KaleidoAgent page.
KaleidoMind
KaleidoMind is an engine for your application. Start with its offline project template, use it through the Desktop App, or embed the package directly.Try the offline starter
npm run start:mock adds a real local model while keeping the wallet simulated.
Through the Desktop App
The fastest path. The Desktop App bundles the engine as in-app chat, and manages the on-device model lifecycle. Switch it on from Settings > Capabilities by selecting Node + Mind or Only Mind.KaleidoMind depends on a local AI runtime and may not be available on Windows yet. Every trading and node feature works without it, so run the app in Only Node mode if Mind is unavailable on your platform.
In your own Node.js app
@qvac/sdk is an optional peer dependency, so the engine also runs without it against a mock provider. The @kaleidorg/mind README has the quickstart, and the kaleido-mind repository carries runnable examples (examples/node-minimal, examples/rgb-agent).
From source, for development
apps/cli handles on-device model management and runs the agent directly: