Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Description from the maker (original English)
Perceptual visual regression, image evidence inspection and bounded decision proposals.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
The maker has not listed install details in the registry. See the maker’s README below.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified with the GitHub account Tavrin, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
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It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.3.0) reached the registry 28 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Rust on your computer.
In the same category: Figma Context MCP, Claude Real Video, Figma MCP Server
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Let any LLM watch a video locally — and search everything it has ever watched.
Figma’s official server gives AI your design data so it can turn designs into code or describe them accurately. Connects to Figma’s cloud.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
MCP Registry: io.github.Tavrin/saccade
saccade is a visual and performance evidence tool for humans, CI and AI agents. It measures perceptual differences, locates them in measured regions (with optional advisory observations), and checks them against the thresholds and policies you declare. It writes offline HTML reports and versioned JSON. Performance conclusions require comparable captures, timing provenance and repeat evidence. Only a human can approve a baseline.
saccade demo --out saccade-demo
saccade view saccade-demo
The demo exits 1 on purpose: it contains changed and missing captures. Open saccade-demo/report/index.html to see the result. The quickstart walkthrough has copyable examples for comparison, exact identity, configuration, evidence export and local review. Not sure which command fits? Use the task map and the five tested guides: visual CI, controlled rendering, document export, media intake and delivery tuning. saccade doctor shows what your install can run.
The local MCP server reads registered capture roots and writes reports under a separate output root. Its tools cannot approve baselines. Agents can inspect bounded results and follow recorded next actions.
saccade mcp --root captures --out-root agent-reports
saccade compare captures/before captures/after --out agent-reports/change --json
See the agent guide and MCP and plugin setup.
The local Playwright package provides toMatchSaccade and capture stabilization. A sweep groups page pairs and records capture failures as failures.
node integrations/playwright/sweep.cjs sweep.json captures capture-options.json
saccade sweep compare sweep.json --captures captures/captures.json --out sweep-report --json
See the Playwright matcher, sweep and CI integration. Sweep needs the optional products feature.
Declared spatial policies distinguish texture_noise_only from systematic_shift. Required-effect checks can fail on an empty footprint; capture layers restrict measurement scope and fixed-camera sequences measure temporal stability. Supply the policies and capture provenance with your inputs.
saccade compare before after --config render-evidence.toml --out render-report --json
saccade experiment sequence before-frames after-frames --fixed-camera --out temporal-report --json
See rendering evidence and engine capture ingestion, temporal settling and one-flag masks.
Audit served formats and search declared encodings for a perceptual target. Local and URL-template adapters record bytes and content types and do not modify originals.
saccade imgtune audit --urls images.txt --accept 'image/avif,image/webp,image/*' --out audit.json --json
saccade imgtune search tuning.json --out tuning-report.json --json
See image tuning. Enable products, plus imgtune-avif for AVIF.
A media record keeps status and provenance for metadata, quality, fingerprints and optional model sections. Disabled or failed sections are recorded as such. The Python package and local HTTP API use the same analysis path.
saccade analyze-media image.jpg --profile cpu-lite --output-size 1200x800 --json
saccade keyframes video.mp4 --out frames --json
See media analysis, Python and HTTP API. Install with pip install saccade-vision (Python 3.10+); the import stays import saccade.
Inspect C2PA credentials, metadata and compression-history indicators without a baseline. Heuristics have stated limits and do not establish a real/fake verdict. GPS disclosure is opt-in; C2PA validation needs credentials.
saccade inspect-image received.jpg --output-size 1600x900 --out inspection --json
saccade inspect-image received.png --hash-index hashes/saccade-hash.v1.json --out indexed-inspection --json
See single-image inspection.
Pick registration, hashes, embedding similarity/search, OCR text differences, no-reference quality or document rasterization to fit the question. Model workflows require supplied pinned artifacts and the relevant features.
saccade compare before.png after.png --align similarity --out aligned-report --json
saccade text before.png after.png --out text-report --json saccade assess image.jpg --out quality-report --json
See choosing a comparison, registration, hashing, embeddings and search, OCR, quality and documents.
Compare supplied timing sidecars using paired statistics and uncertainty intervals, or locate changes in a sequence. Saccade does not run the benchmark; missing or rejected provenance cannot qualify a speedup.
saccade compare before after --out perf-report --json
saccade history onset --store history --json
See paired statistics, change points, identity/performance, timing verdicts, ablation tables and report linking. The performance sidecar kit has fixtures and recipes for producers. Label images can be scored with mask metrics, boxes exchanged as COCO or YOLO (box interchange), and extracted video frames described by a frame map.
Install with Rust 1.89 or newer:
cargo install saccade --version 0.3.0 --locked
saccade doctor --json
To build this checkout, use cargo install --locked --path crates/saccade. Release archives include checksums, licences and third-party notices. See release instructions.
| Cargo features | Default? | Purpose and requirements |
|---|---|---|
compression, parallel, graphics | Yes | FLIP, compression scores, graphics and temporal measurements; CPU processing. |
ai, evaluation | Yes | Provider review adapters and evaluation; calls require explicit authorization and budgets. |
workbench, mcp | Yes | Local report browsing and bounded agent tools. |
assist | No | Experimental explain, mask audit, visible-condition checks and batch advice. |
products | No | Sweep, image tuning, design-source and notifier adapters. Browser captures separately need Node.js and Playwright. |
imgtune-avif | No | AVIF encoding/decoding; system dav1d >=1.3.0 development library and pkg-config. |
semantic-regions, embeddings, local-models | No | Pinned CPU model artifacts and dynamically loaded ONNX Runtime 1.22 (API 22). Runtime/model pulls are explicit provisioning operations; analysis never downloads them. |
ocr, ocr-provider | No | Local PP-OCRv5 Latin with pinned models/runtime; separately opt-in hosted document OCR with spend/egress controls. |
documents, credentials | No | SVG/PDF rasterization and offline C2PA validation. |
media-http | No | Bounded URL inputs for media analysis; network fetches require an explicit URL input. |
local-vlm, vision-providers | No | Configured local/hosted vision adapters; observations remain advice. |
geometry, dense-motion, prechecks, schema | No | Mesh measurements, dense motion, experimental safety/accessibility checks and schema generation. |
Video extraction invokes external ffmpeg and ffprobe; neither is bundled. See model/runtime provisioning and AVIF prerequisites. Default comparisons need no provider account or GPU. Add optional features with cargo install ... --features products,ocr, for example.
| Crate | Purpose |
|---|---|
saccade-core | Shared image measurements, evidence contracts and Rust workflows. |
saccade-print | ICC-managed print raster comparisons and diagnostics. |
saccade-geo | Native TIFF measurements with grid and nodata metadata. |
saccade-a11y | Accessibility pre-checks on declared regions or on regions it finds itself. |
saccade | Command-line interface and MCP server. |
saccade-py | Python bindings for shared measurements. |
With the prechecks feature, a11y auto finds text and UI regions in an image and checks them, offline:
saccade a11y auto screenshot.png --out accessibility-report
Each qualification covers only the recorded contract and evidence. A passing score does not prove correctness or that a difference is invisible.
| Metric or algorithm | Qualification status and scope |
|---|---|
| Native decoded-sample identity | Exact equality contract; covers only supplied, complete pairs. |
| NVIDIA FLIP / HDR-FLIP | Reference-backed implementation; viewing conditions and HDR mapping must be declared. |
| SSIMULACRA2 / Butteraugli 0.9.3 | Reference checks recorded; perceptual targets are user policy. See implementation evidence. |
| ColorVideoVDP, numerical buffers, motion and mesh distances | Declared display/unit/frame/camera contracts; fixture checks do not qualify a consumer renderer. |
| Registration; aHash/dHash/pHash; FAST/oriented-BRIEF matching | Generated-fixture validation; match confidence is uncalibrated. |
| Embedding similarity and image/text retrieval | Pinned model/export provenance; retrieval calibration remains unqualified. |
| PP-OCRv5 Latin and positional text diff | Generated strict and typographic contracts reviewed; font-specific failures remain. |
| Blur, noise, blockiness, banding, clipping and forensic indicators | Descriptive, content-dependent heuristics; no authenticity qualification. |
| Spatial classes, effect occupancy, layers and temporal tiles | Constructed/fixture contracts; no general renderer or physical-effect qualification. |
| Paired Hodges–Lehmann estimates, bootstrap and change points | Constructed statistical checks; actual timing requires independent qualified runs. |
| Safety/accessibility prechecks | Experimental checks; no certification or formal compliance. |
| AI assist, Jev support and routing (Jev is a decision model from TypeSafe), blind-order handling | Unqualified in this release; experimental. |
| LPIPS, DISTS, MUSIQ (quality-score) | Runs only a reviewed exp
Only the beginning is shown; read the rest in the repo