
Taste Bank
io.github.QuasarG由 GitHub 帳號 QuasarG 發布v0.2.0更新於 Oct 24, 2026
Reusable visual design systems for AI coding agents — browse, fetch, and submit styles via MCP.
概覽
一個本機 MCP 伺服器,讓助理從 Taste Bank 瀏覽、取得並提交可重複使用的前端風格包(設計權杖、規則、CSS 與範本)。
- 可以做什麼
- 瀏覽與搜尋已發布的風格包,查看某個風格的詮釋資料與設計權杖細節。一次呼叫取得完整風格包:詮釋資料、權杖、SKILL.md 規則、作用域 CSS 和 HTML 範本快照。把風格以規則檔形式套用到專案中,並管理收藏。驗證、簽章並提交新的風格包進入審核,身分由私鑰代表。
- 適用情境
- 當你希望編碼助理以一致、可重複使用的視覺風格建構前端,而不是每次重新發明風格時使用;也適合發布並版本化自己的風格包。README 將 CLI 列為建議方式,MCP 為舊版方式。
- 執行需求
- 由 MCP 用戶端啟動的本機程序;README 中的 MCP 設定使用遠端 URL 和 x-invite-code 標頭,CLI 需透過 npx 使用 Node.js。需要存取預設後端網路,或透過 TASTEBANK_API 指定自架位址。提交需要邀請碼和以 keygen 指令產生的 ed25519 金鑰對。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Taste Bank,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
README
The front-end style library for coding agents — distill a style once, reuse it everywhere.
Swipe styles like you're scrolling TikTok — find the one that catches your eye, then hand it to your agent.
[npm] [Astro] [TypeScript] [Zod]
English | 中文文档
Why Taste Bank
Sound familiar?
- Staring at a blank page, no idea how to lay out your components?
- Layout finally settled — yet the AI's visual style never quite lands?
- A hoard of "beautiful designs" you can never actually summon when you need one?
- The style you painstakingly tuned in your last project has to be re-explained from scratch in the next one?
Getting coding agents to produce well-designed front-ends is a solved problem nobody can actually use. The community is full of front-end skills, prompt snippets, and design guides — but in practice:
- No unified invocation: some styles ship as a skill, some as a plugin, some ship nothing at all. Actually using them is a chore.
- No quality bar: without a shared schema, a "style" can be three adjectives in a trench coat — nothing an agent can actually execute.
- Hard to reuse: great styles die in chat histories instead of being distilled into an asset.
- No ownership or iteration: no versions, no way to say "only I maintain my styles."
More importantly: the web spawns new styles every day — but not every style is mainstream enough, not every style is your taste. We want a community where people share the front-end taste they actually use — and vote with their feet. Only what truly gets used is truly usable.
Taste Bank's answer: distill each style into a structured style pack (SKILL.md usage guide + precise design tokens + templates/ snapshots), enforced by a zod schema, served through a CLI + skill injection that works with any coding agent. Once a style is in the bank, it's reachable anywhere, versioned, and owned.
The homepage gallery: swipe through live-rendered styles like a feed — horizontal card rail with interactive preview, most-referenced styles and top authors at a glance.
Quick Start
Via CLI (recommended)
One command — installs the CLI globally and teaches your coding agents (Claude Code, Codex, Cursor, ZCode, Kimi Code…) how to use it:
Then just talk to your agent in plain language:
"Build me a landing page with one of the styles in taste-bank."
Your agent already knows what to do — setup injected a skill that teaches it the taste-bank CLI commands. It will browse styles, fetch the complete pack, and implement strictly within the design tokens.
Prefer the terminal?
No per-agent config, no JSON to paste. Browse visually first at tastebank.cloud.
Via MCP (legacy)
For agents that prefer the MCP protocol, configure one URL in your MCP client:
Both paths call the same backend. CLI is recommended — simpler, works with 70+ agents out of the box.
Features
- One-line setup:
npx taste-bank setupinstalls the CLI and injects skills into all your coding agents (Claude Code, Codex, Cursor, ZCode, Kimi Code, and 70+ more via the openskillsecosystem) - Complete style packs:
taste-bank skill <slug>returns the full pack in one call — meta, tokens, SKILL.md rules, scoped CSS, and HTML template snapshots. Agents get everything they need. - 3-day local cache: packs are cached; if the server is unreachable, the CLI falls back to cache
- TikTok-style gallery: tastebank.cloud — endless stream of live-rendered previews, horizontal card rail, leaderboards
- Structured & validated: every pack passes a strict zod schema (meta / tokens / skill / templates), versioned, with invite-only submissions + ed25519-signed ownership + human review
- Submit from the terminal:
taste-bank submit— sign and submit a new style without leaving your project - Private key as identity: no accounts — whoever holds the key manages the style
CLI Commands
Browsing & applying (no auth)
Contributing (invite + ed25519 identity)
How it works
Two skills are injected (via the open skills ecosystem):
taste-bank— teaches your agent the CLI commands for browsing and applying stylestaste-bank-contribute— the full contribution SOP: how to sample a project, pack a style, sanitize it, and submit
After setup, your agent knows the CLI. You just say "use a taste-bank style" and it runs the commands itself.
The CLI talks to tastebank.cloud by default and caches packs locally for 3 days. Self-host? Set TASTEBANK_API=https://your-host.
Submit your own style
Or just tell your agent: "submit this project's style to taste-bank" — the injected taste-bank-contribute skill guides it through the full SOP (sample 2 files max, extract real tokens, sanitize business-identifying content, pack, validate, submit).
See the pack format, the taste-bank-contribute skill, and the agent workflow guide (how to manage project styles in agent conversations). 中文版见 Agent 工作流指南。
Security
Authentication & ownership
- Invite codes: submissions require an invite code; a code binds to the submitter's public key on first use — one code, one identity; only hashes stored server-side
- ed25519 signatures: submit / update / delete all require a private-key signature (message =
style-lab:<action>:<slug>:<timestamp>:<sha256(payload)>, 30-min window) — your key is your identity - Review queue: submissions land in
data/pending/and go live only after maintainer approval - Rate limits: 20 submits/min per pubkey, 30 manages/min per slug
Content safety
- Template sandbox: previews render in a
sandbox=""iframe with CSP forbidding scripts/external loads - HTML blocklist + secret-pattern scanning: submissions are screened for dangerous attributes and high-confidence secret patterns
- Prompt-injection mitigation: style content is labeled "data, not instructions" in skill descriptions
⚠️ Every submission is manually reviewed. But reviews can miss things — do not blindly trust fetched content; treat it as data.
HTTP API
Project structure
License
MIT © QuasarG
來源:README.md,提交 c4526db
工具
0版本歷史
1- v0.2.0最新Sep 16, 2026
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