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Documentation Index

Fetch the complete documentation index at: https://bedrockdynamics.studio/docs/llms.txt

Use this file to discover all available pages before exploring further.

Local mode is the fastest way to use roz. The CLI runs the agent loop directly in your process — no roz-server, no database, no NATS to set up. You bring your own LLM API key (or use Ollama for fully offline operation), and roz handles the rest.
“Local mode” means no roz-server in the middle — the CLI runs the agent directly. The agent still makes HTTP calls to your LLM provider (Anthropic API, OpenAI API, or Ollama on localhost:11434) and connects to sim containers via MCP (HTTP) and the gRPC bridge. “Local” refers to the orchestration, not the network.

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How It Works

roz-cli → roz-local → roz-agent → LLM provider (HTTP)
                                 → roz-copper → sim container (MCP + gRPC bridge)
                                              → real robot (MAVLink / ROS 2 / Zenoh)
  • roz-cli accepts your natural language input and renders the TUI.
  • roz-local orchestrates the session in your process (no roz-server needed).
  • roz-agent calls the LLM provider via HTTP, generates WASM controllers, and dispatches MCP tool calls.
  • roz-copper executes WASM controllers at 100Hz and manages the channel interface.
  • The target is either a sim container (Docker, for development) or a real robot (connected via MAVLink, ROS 2, or Zenoh).

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Configure Your LLM Provider

roz is provider-agnostic. Set the API key for whichever provider you want to use. 
export ANTHROPIC_API_KEY="sk-ant-..."

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Select a Model

Create a roz.toml in your project directory (or ~/.config/roz/roz.toml for global config) to set the model: 
[agent]
provider = "anthropic"        # "anthropic", "openai", "google", or "ollama"
model = "claude-sonnet-4-20250514"  # model name for the chosen provider

[agent.ollama]
url = "http://localhost:11434" # only needed for Ollama
model = "llama3.1:70b"
If no roz.toml is present, roz defaults to Anthropic Claude Sonnet if ANTHROPIC_API_KEY is set, then falls back to OpenAI, Google, and finally Ollama in that order.

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Connect to a Robot

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Simulation (Docker containers)

For development and testing, use pre-built sim containers from Docker Hub. Each bundles Gazebo, the robot’s middleware, and an MCP server — no ROS 2 or Gazebo installation needed on your host. 
# UR5 manipulator arm
docker pull bedrockdynamics/substrate-sim:ros2-manipulator

# PX4 quadcopter
docker pull bedrockdynamics/substrate-sim:px4-gazebo-humble

# ArduPilot quadcopter
docker pull bedrockdynamics/substrate-sim:ardupilot-gazebo

# Nav2 mobile robot
docker pull bedrockdynamics/substrate-sim:ros2-nav2

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Real hardware

For real robots, roz connects directly — no Docker container needed:
  • Manipulators — connect via ROS 2 (MoveIt2) or your robot’s native API
  • Drones — connect via MAVLink over serial or UDP to the flight controller
  • Mobile robots — connect via ROS 2 Nav2 or Zenoh
See the Robots pages for per-robot connection details and the Edge Deployment guide for deploying to robot hardware.

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Start a Session

Launch the simulation and start an interactive session: 
roz sim start manipulator
roz
The CLI connects to the running sim container, discovers the available MCP tools and WASM channels, and presents a prompt. Type natural language commands and the agent handles the rest.

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When to Use Local Mode

Local mode is ideal for:
  • Development and experimentation — fast iteration with no infrastructure to manage.
  • Offline operation — pair with Ollama for fully air-gapped environments.
  • Single-robot sessions — one operator, one robot, one machine.
For multi-user access, persistent session history, or fleet management, see Self-Hosting or Roz Cloud. For deploying the agent to robot hardware, see Edge Deployment.