vector-mirror
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@vector-mirroranalyze layout of my dashboard SVG"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Mirror — a deterministic SVG perception eye for LLM agents
Mirror renders SVG in a real browser and reports what is actually where — in grid cells and W3C color names, with prose and structured output — and it never guesses. Spatial layout constraints become unit tests. And every tool description is a claim the server proves about itself. Built for agents that can't afford to hallucinate coordinates.
What is this?
When an LLM agent edits an SVG, how does it know whether the change worked? Today it either guesses from the source text (and hallucinates positions, because layout is a render-time property, not a source property) or it takes a screenshot and guesses from pixels (and burns tokens on a vision round-trip that still can't name a color or address a region precisely).
Mirror is the third option: a measuring eye. It is a sensory organ for LLMs, not a tool with a purpose. It perceives and measures; it never interprets, decides, or acts — the brain (the LLM or you) does that. The eye has three tissues:
Tissue | What it does |
Retina (measurement) | renders the SVG in real Chromium and measures geometry, colors, visibility |
Mouth (utterance) | says what it saw — |
Package insert (self-description) | explains the organ to a stranger brain: every tool description is a machine-verified claim |
Because the measurement runs in a real browser engine, Mirror sees what the browser sees — including things the SVG source never tells you.
Related MCP server: canvas3d-mcp
Killer demo: the perceive → constrain → correct → compare loop
A cold agent (no source code, MCP only) built a 17-element mission-control panel and verified it to an exact stop-condition. Here is the loop, with real outputs from that session:
# 1 — INSPECT: see the layout in LLM grammar (no constraints checked yet)
inspect(svg)
→ scene: 16 elements, grid 16×10, canvas_validity: valid
e.g. { id: "led-ok", tag: "circle", cell: "B3", color: "lime" }
colors come out as W3C NAMES, never hex.
# 2 — CONSTRAINTS: ask the vocabulary (it is finite and closed)
constraints()
→ 11 types. RIGHT-OF / BELOW deliberately do NOT exist
(use LEFT-OF / ABOVE with swapped operands).
# 3 — ANALYZE: turn layout intent into unit tests
analyze(svg, ["#title CENTERED-IN #frame", "#led-ok ABOVE #led-warn", ...16 constraints])
→ PARTIAL: 2 unchecked SUBJECT_TIME_VARIANT
"#beacon has an animated r → not measurable; geometrically satisfied @t0 (bbox …)"
# the eye refuses to guess about an animated value. It says so, with a reason code.
# 4 — fix, re-analyze until PASS (convergence is tracked, not vibes)
analyze(svg_v3, [...], previousIssueCount: N)
→ PASS (corrections == [] && unchecked == [] && canvas_validity == valid && diff == [])
# 5 — SNIPER LOOP: pin a baseline, edit, catch regressions in one call
bookmark("panel-pass", analysisId)
compare(sabotaged_svg, [], "panel-pass")
→ FAIL: FARBÄNDERUNG orange→crimson + VERSCHOBEN D7→H8
with ready-to-apply fixes: { x: 262→182, y: 372→324 }
# exactly the two injected faults. Nothing more, nothing less.The agent's verdict, verbatim: "In 13 calls it never once guessed, lied, or made me guess.
analyze landed on the first try. Lost diagnostic loops: 0." — 8.5/10.
Features — the honesty axes
Mirror's differentiator is not what it measures but that it is honest about what it cannot.
Capability | What it gives the agent | Honest about |
Grid grammar | every element addressed by cell ( | measurement space is the viewBox, declared |
W3C color names |
| nearest-name snap is named as such |
Spatial constraints |
| unknown types → |
Diff vocabulary | finite, typed: | — |
State axis | flags elements whose visibility depends on interaction |
|
Media axis | flags viewport/media-dependent measurement |
|
Motion axis | animated geometry → |
|
Paint truth | ink outside the geometric bbox (glow/shadow/blur) is flagged |
|
Convergence |
| — |
The rule, stated once: the eye measures gaps; the brain prescribes corrections. Mirror never
clamps, smooths, or invents a value to please you. If it can't measure, it says not_measurable.
Why not screenshots?
A whole field exists for "show the agent the UI" — screenshot MCPs, SVG rasterizers, pixel-diff
regression (Percy, BackstopJS, Playwright snapshots), accessibility-tree snapshots. They all share
one limit: they hand the agent pixels (or structure) and the agent still has to guess. A
screenshot can't be addressed (which region?), can't name a color precisely, can't tell you
whether an element is measurably inside a frame or just looks inside, and can't say "I don't
actually know — this is animated." (A 24-source competitive scan found no tool that combines
LLM-grammar SVG perception, declared honesty axes, and proven tool descriptions.)
Mirror replaces the pixel guess with measured render truth in a grammar LLMs read natively — no image modality, no vision round-trip, no hallucinated coordinates.
Quickstart
Requirements: Node ≥ 18. Mirror renders in real Chromium via Playwright, so a browser binary is needed once.
# install the Chromium engine Mirror measures with (one-time)
npx playwright install chromiumRun as an MCP server — add to your client's MCP config (Claude Desktop, etc.):
{
"mcpServers": {
"vector-mirror": {
"command": "npx",
"args": ["-y", "vector-mirror"]
}
}
}On initialize, the server hands your agent a full Quickstart: the workflow, the constraint
grammar, four verified gotchas, a glossary, and the exact stop-condition — so a cold agent is
productive with zero source reading (this is measured; see The Proof).
First call to try: vector_mirror_inspect with an SVG string → you get the scene in grid
grammar. Then vector_mirror_constraints for the vocabulary, then vector_mirror_analyze.
The Proof
Mirror does not ask for trust; it earns it. Three pieces of evidence:
1 · Cold-consumer love metric
A cold agent (MCP only, no source) built and verified a 17-element panel in 13 tool calls with 0 lost diagnostic loops, scoring 8.5/10 with the reason "never once guessed, lied, or made me guess." The built-in sabotage test caught exactly the two injected faults, with ready-to-apply fix numbers. The one point deducted was an honestly-reported design seam — Mirror reports its own weaknesses too.
2 · Multi-model convergence
13 cold agents across 5 model families (Haiku, Sonnet, Opus, Gemini, Codex) consumed the server independently. Median love 8.0/10; substantive lost loops near zero. Agents guided through the MCP layer did not fall into the traps that un-guided raw-API users did — the guidance layer measurably works.
3 · Machine-proven tool descriptions + anti-circular self-test
Every sentence the server ships — tool descriptions, quickstart, glossary — is projected from one
source (src/interface/claims.js) and is a probe-backed claim (tests/relais_red/). A
mutation in the shipped text turns a test red. On top of that, a 5-fixture self-test runs
anti-circularly — against spec-derived expected values, never against the server's own stored
output. As one consumer put it: "that is the sentence that actually justifies trust."
Determinism: byte-identical input (sanitized DOM, time, selector) → byte-identical output, for a pinned Chromium engine. Verified by a dedicated determinism suite (including an anti-false-green mutation) and property-based fuzzing (
fast-check).
Architecture — three tissues, one organ
┌─────────────────────────────────────────┐
raw SVG ──────▶ │ RETINA sanitize → real Chromium │ measured truth
│ (src/adapters/renderer, src/core) │ (geometry, color,
│ hexagonal: core is import-free │ visibility, paint)
└───────────────────┬─────────────────────┘
▼
┌─────────────────────────────────────────┐
│ MOUTH prose + structured │ two projections
│ (src/adapters/emitter) │ of ONE truth
└───────────────────┬─────────────────────┘
▼
┌─────────────────────────────────────────┐
│ PACKAGE INSERT tool descriptions + │ every claim
│ quickstart (src/interface/claims.js) │ is proven
└─────────────────────────────────────────┘Retina: DOMPurify sanitize → headless Chromium (Playwright) →
getBBox/getBoundingClientRect+ computed style → quantized onto a letter-digit grid → AABB constraints.Hexagonal contract: all measurement lives in the adapter; the core (grid / arbitrate / diff / palette) imports nothing from adapters or interface. Reference truth comes from outside, never from the tool's own past output (anti-circular).
Tools:
inspect,constraints,analyze,compare,bookmark,palette,arrange,status,selftest.
Honest Limitations
Mirror's promise is "the eye does not lie about what it claims to see, and does not stay silent about what it cannot see." That means stating the blind spots plainly:
Pinned-engine determinism. Byte-identity holds for a pinned Chromium version. Cross-version bit-stability is a standing, not-yet-closed watch.
Measurement space is the viewBox, not CSS pixels. A visually distorted shape (round in viewBox, oval on screen) measures by its viewBox geometry. Declared, but easy to forget.
Display caps.
inspect/analyzeshow up to 7 elements; the rest are counted insuppressedbut not individually addressable (no paging cursor yet). Hard limits: 500 DOM nodes / 100 KB.Geometry-only motion flag (today). The motion axis flags clock-rooted SMIL geometry; a purely blinking (
opacity) or color-animating (fill) element can currently return a static value. On the roadmap.Constraints check the geometric bbox, not
visual_bbox— paint overflow is reported separately, not folded intoINSIDE.Prose channel language. The structured/tool layer is English; the layout-prose vocabulary is currently German. Full English prose projection is a v1.1 item.
Mask/clip geometry,
<use>shadow edges and a few other surfaces are over-flagged (indeterminate/not_measurable) rather than silently guessed.
We list these because honesty is the product. Several are tracked as issues — see the roadmap.
Roadmap (teaser)
The eye is declared healthy on its known blind-spot denominator; the growth epoch is open. Next super-powers (deterministic + non-generating, like an eye gaining night-vision or zoom):
a paging cursor /
limitssection so suppressed elements are addressable;a full paint/opacity/fill time axis (not just SMIL geometry);
machine-readable measurement constants (tolerance, grid rule, color-snap distance);
the optional docking station — a deterministic correction loop that drives one measured gap to a brain-given goal (lives downstream of the eye, physically separate);
full English prose projection (v1.1).
License
MIT © c64dos-png
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