Flit Physics

Registre officiel Jeux, sport et divertissement

Tiny sphere-physics engine for three.js games: spawn, step, raycast, InstancedMesh-ready positions

Installation

Ajoutez ceci à la configuration MCP de votre client (Claude Desktop : claude_desktop_config.json ; Cursor : .cursor/mcp.json ; VS Code et les autres utilisent la même forme « mcpServers »).

NPM package flit-physics
Claude Code
claude mcp add flit-physics -- npx -y flit-physics@0.2.2
Configuration JSON (Claude Desktop, Cursor, VS Code)
{
    "mcpServers": {
        "flit-physics": {
            "command": "npx",
            "args": [
                "-y",
                "flit-physics@0.2.2"
            ]
        }
    }
}

Documentation

Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.

Sommaire
  1. Flit
  2. What's in the box
  3. For agents
  4. Usage
  5. Develop
  6. Benchmarks
  7. Roadmap
  8. License

Flit

Flit is a tiny little physics engine for 3js. It doesn't do much yet! but I believe!

Spheres, collisions, raycasts, gravity, and a spatial-hash broadphase — nothing more, on purpose. All simulation state lives in flat Float32Arrays (structure-of-arrays), so the CPU path doubles as the reference implementation for a future WebGPU compute backend: same buffers, same kernels, no re-architecting.

What's in the box

  • World — point-sphere particles, semi-implicit Euler integration, impulse + positional-correction contact solver, infinite ground plane. Bodies that stay quiet SETTLE (per-body sleep driven by a stiction threshold), so resting piles cost ~nothing; a fast-enough impact wakes them, a slow push is held by static friction.
  • Heightfield — 2.5D terrain as a grid of height posts, no meshing: bilinear height + central-difference normals sampled directly for collision, and a 2D Amanatides-Woo DDA for raycasts (index: -1).
  • Raycast — Amanatides-Woo voxel walk over the broadphase grid; candidates from the 3x3x3 block around the walked path so corner clips are never missed. Differential-tested against a brute-force oracle.
  • SpatialHash — uniform grid broadphase keyed by Morton (Z-order) cell codes. This is the Euclidean cousin in the LSH family: MinHash buckets documents by Jaccard similarity; this buckets positions so nearby points collide in the same bucket. Morton keys are bijective (no hash-collision pair bloat), invertible (no side table), and locality-ordered for a future sorted-array GPU backend.
  • Distance & bit utilities — squared Euclidean/L1/Minkowski/L∞/Hellinger/ chi-square/KL distances (ported from FLANN), Morton (Z-order) keys, float bit-flips for radix sorting, octagonal approximate distance. See THIRD_PARTY_NOTICES.md for provenance and licenses.

For agents

Building a little three.js game or demo? Two ways in:

  • Skill: skills/flit/SKILL.md — copy the skills/flit/ directory into your agent's skills path (e.g. .claude/skills/, ~/.code_puppy/skills/). It carries the 30-second integration recipe, the MCP option, measured performance envelope, and contributor rules.
  • MCP server (no code needed): npm run mcp, or point your client at it:
{
  "mcpServers": {
    "flit": {
      "command": "npx",
      "args": ["vite-node", "mcp/server.ts"],
      "cwd": "<path-to-this-repo>"
    }
  }
}

Tools: flit_info, flit_reset (gravity/restitution/ground/bounds/ settleSpeed/heightfield), flit_spawn (rain/explosion/grid/fountain presets), flit_add_particles, flit_step, flit_state, flit_raycast — step/state return flat xyz positions shaped for InstancedMesh syncing plus settledCount, so you can watch a pile go quiet.

Usage

npm i flit-physics
import { World } from 'flit-physics';

const world = new World({ restitution: 0.4 }); // gravity and a floor at y=0 included

const ball = world.addParticle({ position: [0, 10, 0], radius: 0.5, mass: 1 });

// fixed timestep, e.g. from your rAF loop
world.step(1 / 60);

// sync to three.js: positions is a live Float32Array, 3 floats per particle
mesh.position.set(
  world.positions[ball * 3],
  world.positions[ball * 3 + 1],
  world.positions[ball * 3 + 2],
);

Terrain and sleep are one option each:

import { Heightfield, World } from 'flit-physics';

const terrain = new Heightfield({ rows: 64, cols: 64, cellSize: 1, heights });
const world = new World({ groundY: null, heightfield: terrain });
// bodies collide with the terrain and settle on it;
// world.raycast(...) reports terrain hits as index -1

// sleep is on by default (settleSpeed 0.01 m/s); opt out per world:
const wideAwake = new World({ settleSpeed: 0 });

Develop

npm install
npm test        # vitest
npm run build   # tsc -> dist/
npm run bench   # broadphase + full-step micro-benchmarks
npm run demo    # three.js demo scene (vite dev server)

Benchmarks

Deterministic seeds; numbers from a local dev machine, recorded at commit time (see commit messages for the full series, including rejected designs).

  • bench/broadphase.bench.ts — broadphase only, N=4096: xor-hash 3.4–3.7 ms (444 pairs, ~90% collision bloat) → Morton keys with ordered probing 3.5–3.7 ms (234 pairs, exact).
  • bench/world.bench.ts — full World.step, N=1024: xor-hash 0.85 ms/step → Morton ordered-probing 0.83 ms/step → 0.93 ms/step with the sequential-impulse velocity solver (4 iterations + LUT friction). Exact keys, real contacts, +11%.
  • bench/scaling.bench.ts — two regimes. Fixed box (density rises): pairs scale ~N² from crowding physics. Scaled box (constant spawn density): flat O(N) ≈ 1.2 ms per 1000 through N=8000 while bodies are scattered. With gravity on, everything rains into a dense floor pile over ~2-4s (WARMUP=240 to reproduce) — and since 0.3.0 the pile SETTLES: 34.2 → 9.2 ms/step at N=8000 (3.7x, inside the 60fps budget) as bodies fall asleep bottom-up. Settled bodies are skipped by integration, planes, and mutual contacts until a >1 m/s impact wakes them. (docs/issues/001 — resolved; brief kept for the analysis and the remaining ideas: warm starting, adaptive iterations.)
  • bench/raycast.bench.ts — 2000 seeded rays at N=4096: 63–68 µs/ray (vs ~160 µs for a brute-force O(N) oracle at the same density; the grid walk pulls further ahead as N grows).
  • bench/morton-libs.bench.ts — codec bake-off vs npm libs (npm run bench:libs): ours 3.8 ns/encode, fast-morton MB 26.1, fast-morton LUT 43.8, @thi.ng/morton 539.9. In-house wins; the libs stay as devDependencies purely so the bake-off stays runnable.
  • bench/threaded.bench.ts — WorkerWorld over a real worker thread (SAB ping-pong): kick() costs 0.014 ms on the main thread; with a 4 ms render workload a frame costs 8.84 ms pipelined vs 14.96 ms serial at N=8192 (113 fps vs 67). At N=1024 the 0.8 ms step hides entirely behind render (4.03 vs 4.80 ms).
  • Rejected on measurement (see commits): 63-bit BigInt keys (13× alloc regression); sorted-array + binary-search broadphase (1.4× slower than Map probing in JS — negative result recorded).

Roadmap

  • Morton-ordered broadphase cells — done, measured, shipped
  • three.js demo scene — npm run demo, 220 balls in a box (?terrain for heightfield hills, ?n=8000 for load testing)
  • Worker-threaded stepping — WorkerWorld: kick/waitForUpdate, SAB ping-pong zero-copy rendering
  • Settled-pile solver cost — per-body sleep shipped (34.2 → 9.2 ms at N=8000); issue brief kept for the remaining ideas (warm starting, adaptive iterations)
  • Heightfield terrain — shipped, no meshing; hooks left for more collider shapes
  • Raycast coarse occupancy filter (skip empty space faster) if ray-heavy workloads show up — see commit 3173a6f for the analysis
  • WebGPU compute backend once the CPU reference settles

License

MIT — see LICENSE. Third-party portions and their licenses are listed in THIRD_PARTY_NOTICES.md.

Questions fréquentes

Qu'est-ce que Flit Physics ?

Tiny sphere-physics engine for three.js games: spawn, step, raycast, InstancedMesh-ready positions

Comment installer Flit Physics ?

Il s'exécute sur votre machine. Dans Claude Code : claude mcp add flit-physics -- npx -y flit-physics@0.2.2. Pour les autres clients, collez la configuration JSON de cette page dans leurs réglages MCP.

Faut-il une clé API pour Flit Physics ?

Son entrée au registre n'indique aucune clé ni secret obligatoire. Certaines fonctions peuvent tout de même demander un compte auprès du service auquel il se connecte.

Flit Physics est-il open source ?

Oui. Son code est sur GitHub sous licence MIT.

Qui maintient Flit Physics ?

Il est publié par brashler. AI.tn le référence sans le maintenir ni le recommander.

Issu du registre MCP officiel. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.