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Tiny sphere-physics engine for three.js games: spawn, step, raycast, InstancedMesh-ready positions
About
Tiny sphere-physics engine for three.js games: spawn, step, raycast, InstancedMesh-ready positions
Security Report
Flit is a well-engineered physics engine MCP server with clean architecture and proper input validation. The codebase demonstrates solid security practices: no hardcoded credentials, safe use of external libraries, and appropriate permission scoping. Minor code quality observations around error handling and logging do not materially impact security. Supply chain analysis found 1 known vulnerability in dependencies (1 critical, 0 high severity). Package verification found 1 issue.
7 files analyzed · 6 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
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How to Install
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-brashler-flit": {
"args": [
"-y",
"flit-physics"
],
"command": "npx"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
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.mdfor provenance and licenses.
For agents
Building a little three.js game or demo? Two ways in:
- Skill:
skills/flit/SKILL.md— copy theskills/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— fullWorld.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=240to 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, shippedthree.js demo scene—npm run demo, 220 balls in a box (?terrainfor heightfield hills,?n=8000for load testing)Worker-threaded stepping—WorkerWorld: kick/waitForUpdate, SAB ping-pong zero-copy renderingSettled-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
3173a6ffor 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.
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