Tiny sphere-physics engine for three.js games: spawn, step, raycast, InstancedMesh-ready positions
Runs on your machine from its package; the steps are below.
At most: creates or changes data: records, files, settings.
Odel charges nothing per call. The publisher may charge for its own service.
Runs locally over stdio
This server isn't hosted — your MCP client launches it from a package registry. Use one of the commands below, or drop the config into your client (e.g. Claude Desktop).
Run
npx -y flit-physics
MCP client config
{
"mcpServers": {
"flit-physics": {
"command": "npx",
"args": [
"-y",
"flit-physics"
]
}
}
}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.
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).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.THIRD_PARTY_NOTICES.md for provenance and licenses.Building a little three.js game or demo? Two ways in:
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.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.
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 });
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)
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).npm run demo, 220 balls in a box
(?terrain for heightfield hills, ?n=8000 for load testing)WorkerWorld: kick/waitForUpdate, SAB
ping-pong zero-copy rendering3173a6f for the analysisMIT — see LICENSE. Third-party portions and their licenses are listed in
THIRD_PARTY_NOTICES.md.