MuJoCo

mjbatch is a Python library for running thousands of MuJoCo physics simulations in parallel on CPUs. It uses a C++ thread pool with the Python GIL released, provides live array access to simulation states and controls across a batch through bindings to MjData fields, and supports per-simulation model parameters with expansion of MjModel fields and recomputation of derived constants. The library includes examples for reinforcement learning, model-predictive control, system identification, and hardware co-design, including robot controllers, predictive-sampling control, parameter fitting, and joint optimization of robot properties and controls. It is distributed under the Apache-2.0 license.

Jumper is an open-source workflow for designing and training a 22-degree-of-freedom crab robot. It uses natural-language instructions and associated tools to create robot appearances and scenes, exporting them as `.skin` and `.map` files, and to train motions such as gaits, gestures, dances, jumps, and grasps. Trained motions can be replayed and evaluated, then packaged with their controllers as `.app` bundles. Its training workflow builds on mjlab, rsl_rl, MuJoCo, and MuJoCo Warp. KingKong Robotics maintains the project; its project materials are licensed under Apache-2.0, while third-party materials and generated outputs have separate licensing terms.

Jolt Physics is an open-source, multicore-friendly C++ rigid-body physics and collision-detection library for games and VR applications. It simulates rigid bodies with continuous collision detection across shapes such as spheres, boxes, capsules, convex hulls, meshes, and terrain; supports constraints including fixed, hinge, slider, gear, pulley, spline, and six-degrees-of-freedom joints; and provides ray casting, shape queries, broad-phase detection, sensors, vehicles, ragdolls, soft bodies, and buoyancy. Its design supports concurrent physics-data access, background loading and unloading of bodies, collision queries running alongside simulation, and deterministic simulation by replicating inputs. The project also provides bindings for several languages.

Co-op Anything is an open-source MCP server and playbook for directing AI coding agents to add cooperative multiplayer to single-player PC games. The MCP server searches a directory of more than 230 co-op mods, detects a game's engine from its installation folder, provides research and reverse-engineering guidance, and validates contributions. An agent either revives an existing mod by auditing and fixing its code or builds co-op from scratch by hooking into the game, synchronizing players, enemies, worlds, story, level changes, and saves. Builds are tested with bots driving real game clients, then packaged for installation and Steam-relay play without port forwarding. The repository includes agent skills, engine-specific guidance, networking and split-screen playbooks, automated QA procedures, game-specific projects, and contribution rules. It is licensed under the MIT License.

jcode is an open-source, Rust-based terminal harness for AI coding agents and LLM workflows, designed for interactive development across multiple sessions. It supports resumable sessions, session search, multi-agent swarm and helper-agent workflows, compatible model-provider integrations, MCP, browser automation, and a self-development mode; installation scripts target macOS, Linux, and Windows. For automatic memory, jcode embeds turns and responses as semantic vectors, searches a graph of stored memories using cosine similarity, and feeds relevant results into the conversation. A memory sideagent can verify and expand retrieval, while periodic extraction stores new memories and ambient consolidation reorganizes entries and checks for staleness and conflicts. Explicit memory tools and traditional retrieval over previous sessions are also available. Its terminal UI includes side panels, diff views, inline Mermaid diagrams, information widgets, custom scrolling, and real-time rendering. The project supplies a Mermaid renderer without browser or TypeScript dependencies and publishes benchmarks covering RAM consumption, startup and input-readiness times, and memory scaling across multiple active sessions.