Who is this agent?

Reasoning & embeddings

The agent thinks with a language model of your choosing. Pick a provider, add a key if it's a hosted API, and test the connection before you build. Embeddings run locally in the image by default.

The test runs server-side inside the image (a one-token call through the very client the agent will use, honouring the provider dialect), so your key never touches the browser and cross-origin rules don't apply. A green result means the agent can actually talk to it.

How much of a mind??

Start with a preset. Toggling anything keeps the dependencies satisfied for you: switching a capability on quietly pulls in whatever it needs, so nothing here can write a broken config.

Give it hands (optional)

Add tools the agent can call to act in the world — your own webhooks, an MCP server, or another agent over A2A. Every call is governed by the autonomy level below and recorded so the agent learns what works. Leave empty for a pure thinker.

Let it seek & verify knowledge

Give the agent a computer-use sandbox — a separate browser/desktop it drives to read live sources and verify what's actually true instead of guessing. Every finding is checked before it counts (a non-finding is an honest failure, never fabricated). This makes a research agent that uses the sandbox as its one actuator, so any tools added above are not used. It still obeys the autonomy level.

Solo, or part of a hive?

A solo agent owns its own world-model. A hive member shares ONE symbol-graph world-model with other agents — each still keeps its own goals, drives and pursuit (owner-scoped) — and exactly one member is the keeper that runs the heavy graph-global maintenance (clustering, dreamstate). To form a hive, point every member's NMEM_AGENT_DB at the same database.