Windows-first Webots developer toolkit with CLI, MCP server, controller SDK, and bundled benchmarks.
Project description
webots-mcp-kit
webots-mcp-kit is a Windows-first developer toolkit for connecting LLM agents to Webots.
It combines:
- a pip-installable CLI
- an MCP server with Webots session tools
- a controller-side SDK for structured telemetry and manual overrides
- bundled example scenarios and benchmarks
The bundled line follower is not the product itself. It is the first reference example. The toolkit is meant to be reusable across other Webots robots, controllers, and worlds.
Current release
v0.10.3
Current focus:
- Windows-first local development
- Webots
R2025a - direct Webots integration without ROS2
- stable controller-side integration through
ControllerAgent - bundled scenarios plus registry-backed benchmark thresholds
- hosted-safe CI with separate self-hosted runtime smoke
- release pipeline for GitHub Release, TestPyPI, and PyPI
- public-contract regression coverage and external-user onboarding
- MCP reliability for LLM-driven Webots sessions
- zero-to-sim foundations through template-driven project and scenario generation
- standardized runtime artifact and replay bundles for exported sessions
- centralized clean-user acceptance flow for package and publish smoke
Operational runtime model:
interactive-webotsis the single supported runtime execution path for real Webots sessions, benchmarks, and runtime smoke- Windows service mode is not a supported runtime path at the active pre-
v1.0.0contract line
Current support
Supported now:
- Windows
- Webots
R2025a - Python
3.11+ - interactive self-hosted runtime through the
interactive-webotsrunner label as the only supported runtime execution model - experimental-foundation zero-to-sim commands:
project/scenario/import/replay
Not supported in the pre-v1.0.0 line:
- Windows service runner runtime
- Linux/macOS runtime support
- ROS2 integration
- multi-robot orchestration
Bundled scenarios
line-follower- camera-based line tracking
- example world:
examples/line-follower
obstacle-avoidance- proximity-sensor obstacle avoidance
- example world:
examples/obstacle-avoidance
waypoint-nav- fixed-waypoint navigation in an open arena
- example world:
examples/waypoint-nav
Install
Use an isolated virtual environment. The toolkit depends on mcp, which may pull shared web stack packages into your global Python install.
python -m venv .venv
.venv\Scripts\Activate.ps1
pip install webots-mcp-kit
Development install:
python -m venv .venv
.venv\Scripts\Activate.ps1
pip install -e .[dev]
Optional CI or slow-machine tuning:
$env:WEBOTS_KIT_SESSION_START_TIMEOUT='90'
Quick start
I want to connect an agent to Webots
webots-kit doctor
webots-kit session start --scenario line-follower --controller example --mode fast --render off
webots-kit mcp serve
webots-kit benchmark list
webots-kit benchmark run line-follower --controller example --output .\report.json --duration-s 3
webots-kit benchmark report .\report.json
I want to integrate my own controller
webots-kit controller scaffold .\controllers\my_agent.py --scenario line-follower
webots-kit controller validate .\controllers\my_agent.py --scenario line-follower --strict --json
webots-kit benchmark run line-follower --controller .\controllers\my_agent.py --output .\report.json
I want to generate a scenario from a spec
webots-kit project init .\my-webots-project
webots-kit scenario init .\my-webots-project\scenarios\warehouse-demo --template epuck-waypoint
webots-kit scenario validate .\my-webots-project\scenarios\warehouse-demo\webots-kit.scenario.json
webots-kit scenario build .\my-webots-project\scenarios\warehouse-demo\webots-kit.scenario.json
webots-kit scenario doctor .\my-webots-project\scenarios\warehouse-demo\webots-kit.scenario.json
I want to import and replay
webots-kit project import --world .\worlds\demo.wbt --controller .\controllers\demo_agent.py
webots-kit session export <session-id> --output .\artifacts\exports\<session-id>
webots-kit session replay .\artifacts\exports\<session-id>
CLI surface
webots-kit doctor [--json]webots-kit session start --scenario <name> --world <path> --controller <path-or-id> [--robot-name <name>] [--robot-def <def>] [--mode fast|realtime|pause] [--render on|off]webots-kit session inspect --session <id>webots-kit session logs --session <id> [--name <file>] [--tail <n>]webots-kit session export <id> [--output <path>]webots-kit session replay <export-path> [--json]webots-kit session stop --session <id>webots-kit benchmark listwebots-kit benchmark run <scenario> --controller <path-or-id> --output <report.json> [--duration-s <seconds>] [--world <path>] [--robot-name <name>] [--robot-def <def>]webots-kit benchmark report <report.json>webots-kit controller validate <path> [--scenario <name>] [--strict] [--json]webots-kit controller scaffold <path> [--scenario <name>] [--force]webots-kit project init <path> [--name <name>] [--force]webots-kit project import --world <path> --controller <path> [--project-root <path>]webots-kit scenario init <path> --template <template> [--force]webots-kit scenario validate <spec-path> [--json]webots-kit scenario build <spec-path> [--force]webots-kit scenario describe <spec-path>webots-kit scenario doctor <spec-path> [--json]webots-kit mcp serve
Supported zero-to-sim templates:
epuck-arenaepuck-line-trackepuck-waypointepuck-obstacle-course
Foundation status for the zero-to-sim surface:
- CLI command names are now treated as stable
- the underlying JSON
ScenarioSpecschema is stillexperimental-foundation - the schema is documented and supported, but not yet frozen for additive refinement before
v1.1.0
Controller integration
There are two supported usage paths:
- bundled example controllers under
examples/ - user-supplied Python controllers that integrate with
ControllerAgent
The public controller-side entrypoint is ControllerAgent.
The stable public contract is:
ControllerAgent.from_robot(...)begin_step()report_step(...)
Minimal integration shape:
from controller import Robot
from webots_mcp_kit.agent import ControllerAgent
robot = Robot()
agent = ControllerAgent.from_robot(robot, default_camera="camera")
while robot.step(int(robot.getBasicTimeStep())) != -1:
override = agent.begin_step()
# apply your control logic, optionally overriding wheel commands
agent.report_step(
sensors={},
metrics={},
actuators={},
camera_frames=None,
)
Use webots-kit controller validate <path> to check whether a controller follows the expected integration pattern.
Use webots-kit controller scaffold when you want a working starter file based on a bundled scenario.
MCP tools
webots_session_startwebots_session_stopwebots_list_robotswebots_list_deviceswebots_get_statewebots_get_sensorswebots_capture_camerawebots_set_motor_velocitywebots_stepwebots_pause_resumewebots_resetwebots_run_benchmark
Stable payload shapes:
webots_session_start ->stable session/readiness top-level keys with additive extras onlywebots_get_state -> { session, session_state, control_paused, runtime_summary, runtimes }webots_list_devices -> { robot, scenario, devices }webots_get_sensors -> { robot, scenario, state, sensors, metrics, actuators, meta }webots_capture_camera -> { path, width, height }webots_run_benchmark ->stable benchmark report top-level keys with additiveextra_metrics- failed MCP tool calls ->
{ ok: false, error: { code, message, details, retriable } } - existing MCP/runtime failure codes will not be renamed before
v1.0.0; new codes may only be added
Reference docs:
- Onboarding flows
- First hour guide
- MCP contracts
- Self-hosted runtime smoke
- Custom controller integration
- Add a new scenario
- Zero-to-sim guide
- Project import and session replay
- Failed runtime smoke triage
- PyPI install and upgrade
- Release checklist
- Runner maintenance
- Packaging verification
Testing
Unit tests:
python -m pytest -q
Hosted-safe smoke tests:
$env:WEBOTS_KIT_RUN_SMOKE='1'
python -m pytest -q -k mcp_tool_list_smoke
Full runtime smoke tests with real Webots execution:
$env:WEBOTS_KIT_RUN_RUNTIME_SMOKE='1'
python -m pytest -q -k "session_start_inspect_stop_smoke or benchmark_smoke or generated_scenario_smoke or imported_project_smoke"
The self-hosted GitHub workflow for runtime smoke expects a Windows runner labeled interactive-webots.
That runner must be started from an interactive user session. Windows service mode is not sufficient for Webots runtime smoke because Webots exits during OpenGL initialization before controllers connect.
The self-hosted runtime workflow also auto-triggers for runtime-affecting changes and still supports manual dispatch.
Packaging and release verification are handled by GitHub workflows:
Packaging CIRelease
Troubleshooting
- If
doctorfails, ensureWEBOTS_HOMEis set or Webots is installed inC:\Program Files\Webots. - If MCP or session startup closes immediately, inspect
session logsfor the session artifacts. - Session failures now report structured error codes such as
render-init-failed,agent-connect-timeout, andsupervisor-connect-timeout. - If package installation changes global Python web dependencies, recreate a dedicated virtual environment and reinstall there.
- GitHub-hosted
windows-latestrunners are only used for unit tests,doctor, and MCP handshake smoke. Real Webots runtime smoke is exposed as a separate manual workflow for self-hosted Windows runners with Webots installed. - Runtime-affecting changes now also path-trigger the self-hosted runtime workflow when the
interactive-webotsrunner is available. examples/contains runnable demo assets; benchmark thresholds and pass/fail logic live in the benchmark registry inside the toolkit code.- Wheel installs use bundled package-local scenario assets; source checkouts continue to use repo-local
examples/. - The self-hosted machine standard for runtime smoke is the runner-owned Python install at
D:\actions-runner\python311-shared.
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