diff --git a/alr_envs/examples/examples_metaworld.py b/alr_envs/examples/examples_metaworld.py
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+++ b/alr_envs/examples/examples_metaworld.py
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+import alr_envs
+from alr_envs.meta.goal_and_object_change import MPWrapper
+
+
+def example_dmc(env_id="fish-swim", seed=1, iterations=1000, render=True):
+    """
+    Example for running a MetaWorld based env in the step based setting.
+    The env_id has to be specified as `task_name-v2`. V1 versions are not supported and we always
+    return the observable goal version.
+    All tasks can be found here: https://arxiv.org/pdf/1910.10897.pdf or https://meta-world.github.io/
+
+    Args:
+        env_id: `task_name-v2`
+        seed: seed for deterministic behaviour (TODO: currently not working due to an issue in MetaWorld code)
+        iterations: Number of rollout steps to run
+        render: Render the episode
+
+    Returns:
+
+    """
+    env = alr_envs.make(env_id, seed)
+    rewards = 0
+    obs = env.reset()
+    print("observation shape:", env.observation_space.shape)
+    print("action shape:", env.action_space.shape)
+
+    for i in range(iterations):
+        ac = env.action_space.sample()
+        obs, reward, done, info = env.step(ac)
+        rewards += reward
+
+        if render:
+            # THIS NEEDS TO BE SET TO FALSE FOR NOW, BECAUSE THE INTERFACE FOR RENDERING IS DIFFERENT TO BASIC GYM
+            # TODO: Remove this, when Metaworld fixes its interface.
+            env.render(False)
+
+        if done:
+            print(env_id, rewards)
+            rewards = 0
+            obs = env.reset()
+
+    env.close()
+    del env
+
+
+def example_custom_dmc_and_mp(seed=1, iterations=1, render=True):
+    """
+    Example for running a custom motion primitive based environments.
+    Our already registered environments follow the same structure.
+    Hence, this also allows to adjust hyperparameters of the motion primitives.
+    Yet, we recommend the method above if you are just interested in chaining those parameters for existing tasks.
+    We appreciate PRs for custom environments (especially MP wrappers of existing tasks)
+    for our repo: https://github.com/ALRhub/alr_envs/
+    Args:
+        seed: seed for deterministic behaviour (TODO: currently not working due to an issue in MetaWorld code)
+        iterations: Number of rollout steps to run
+        render: Render the episode (TODO: currently not working due to an issue in MetaWorld code)
+
+    Returns:
+
+    """
+
+    # Base MetaWorld name, according to structure of above example
+    base_env = "button-press-v2"
+
+    # Replace this wrapper with the custom wrapper for your environment by inheriting from the MPEnvWrapper.
+    # You can also add other gym.Wrappers in case they are needed.
+    wrappers = [MPWrapper]
+    mp_kwargs = {
+        "num_dof": 4,
+        "num_basis": 5,
+        "duration": 6.25,
+        "post_traj_time": 0,
+        "width": 0.025,
+        "zero_start": True,
+        "policy_type": "metaworld",
+    }
+
+    env = alr_envs.make_detpmp_env(base_env, wrappers=wrappers, seed=seed, mp_kwargs=mp_kwargs)
+    # OR for a DMP:
+    # env = alr_envs.make_dmp_env(base_env, wrappers=wrappers, seed=seed, mp_kwargs=mp_kwargs, **kwargs)
+
+    # This renders the full MP trajectory
+    # It is only required to call render() once in the beginning, which renders every consecutive trajectory.
+    # Resetting to no rendering, can be achieved by render(mode=None).
+    # It is also possible to change them mode multiple times when
+    # e.g. only every nth trajectory should be displayed.
+    if render:
+        raise ValueError("Metaworld render interface bug does not allow to render() fixes its interface. "
+                         "A temporary workaround is to alter their code in MujocoEnv render() from "
+                         "`if not offscreen` to `if not offscreen or offscreen == 'human'`.")
+        # TODO: Remove this, when Metaworld fixes its interface.
+        # env.render(mode="human")
+
+    rewards = 0
+    obs = env.reset()
+
+    # number of samples/full trajectories (multiple environment steps)
+    for i in range(iterations):
+        ac = env.action_space.sample()
+        obs, reward, done, info = env.step(ac)
+        rewards += reward
+
+        if done:
+            print(base_env, rewards)
+            rewards = 0
+            obs = env.reset()
+
+    env.close()
+    del env
+
+
+if __name__ == '__main__':
+    # Disclaimer: MetaWorld environments require the seed to be specified in the beginning.
+    # Adjusting it afterwards with env.seed() is not recommended as it may not affect the underlying behavior.
+
+    # For rendering it might be necessary to specify your OpenGL installation
+    # export LD_PRELOAD=/usr/lib/x86_64-linux-gnu/libGLEW.so
+    render = False
+
+    # # Standard DMC Suite tasks
+    example_dmc("button-press-v2", seed=10, iterations=500, render=render)
+
+    # MP + MetaWorld hybrid task provided in the our framework
+    example_dmc("ButtonPressDetPMP-v2", seed=10, iterations=1, render=render)
+
+    # Custom MetaWorld task
+    example_custom_dmc_and_mp(seed=10, iterations=1, render=render)