iconserve

iconserve

Open-source icons at predictable URLs

Category
访问服务器

README

IconServe

A free, agent-readable service that aggregates 10,000+ open-source iconsLucide, Heroicons, Tabler, and Simple Icons — and serves them as SVG or PNG at predictable URLs, with keyword + semantic search, an llms.txt, and an MCP server.

Runs entirely within the Cloudflare free tier (Workers + R2 + Workers AI).

How an agent uses it

Need Do this
Embed an icon you know the name of GET /i/{name}.svg (best match) or /icons/{set}/{name}.svg
Find the right icon GET /api/search?q=shopping+cart → names + ready URLs
Read the whole API in one shot GET /llms.txt (or /llms-full.txt)
Native tool calls MCP server at /mcp (search_icons, get_icon, list_sets)
OpenAPI GET /openapi.json

Discoverability surfaces (for crawling/browsing agents)

  • GET /icon/{set}/{name} — crawlable HTML page per icon (preview, usage, JSON-LD ImageObject + breadcrumb). /icon/{name} 302-redirects to the best match.
  • GET /sitemap.xml — every icon page (~10k URLs).
  • GET /robots.txt — explicitly allows AI crawlers (GPTBot, OAI-SearchBot, ClaudeBot, PerplexityBot, Google-Extended, …) and points to the sitemap.
  • Landing page carries WebSite+SearchAction and WebAPI JSON-LD and Open Graph tags.
  • IndexNow: key file served at /{INDEXNOW_KEY}.txt; npm run indexnow pings Bing/Yandex to crawl new or changed URLs instantly (pass paths to submit a subset, e.g. npm run indexnow /icon/lucide/house).

Transforms (query params on any icon URL)

  • color= hex / CSS color / currentColor — e.g. ?color=%23e11d48
  • size= 1..2048 px
  • stroke= 0..20 (line icons)
  • style= e.g. solid (Heroicons), filled (Tabler)
  • format= svg | png

Example: /i/shopping-cart.svg?color=crimson&size=48&stroke=1.5

Architecture

Build (offline, on your machine — no Cloudflare cost)
  scripts/ingest.mjs  → data/pack/icons.json  (id → normalized SVG, currentColor-driven)
                        data/pack/catalog.json (names, tags, aliases, license, styles)
                        data/pack/corpus.json  (search text per icon)
  scripts/embed.mjs   → data/pack/embeddings.bin  (10k × 384, bge-small-en-v1.5)
                        data/pack/embed-index.json

Cloudflare
  R2 (ICONS)   holds the 4 packed artifacts; loaded once per isolate into memory
  Workers AI   embeds ONLY the query string at search time (same 384-dim model)
  Worker       routing, color/size/stroke transforms, PNG (resvg-wasm), search, MCP, docs
  Assets       public/index.html landing page

Semantic search = keyword ranking fused (reciprocal-rank fusion) with cosine similarity over the in-memory embeddings. No Vectorize, no per-vector billing, no dimension cap. If embeddings.bin is absent, search gracefully falls back to keyword-only.

Local development

npm install
npm run build:data     # ingest + embed  (embed downloads a ~40MB model once)
npm run upload:r2      # push artifacts into the LOCAL R2 store
npm run dev            # http://localhost:8787

In wrangler dev --local the Workers AI binding is offline, so search runs keyword-only locally. Semantic search activates once deployed (or when running against the remote AI binding).

Deploy (Cloudflare free tier)

wrangler login         # one-time, opens a browser
npm run deploy         # creates the R2 bucket, uploads artifacts, deploys the Worker

npm run deploy runs scripts/deploy.mjs: it creates the iconserve-icons bucket (idempotent), uploads the four artifacts to remote R2, then wrangler deploy.

Adding / updating icon sets

Edit scripts/lib/sets.mjs, then re-run npm run build:data && npm run upload:r2 (local) or npm run deploy (remote). Set priority for /i/{name} best-match is DEFAULT_SET_ORDER in wrangler.toml.

Licensing

Icons are redistributed under their original permissive licenses: Lucide (ISC), Heroicons (MIT), Tabler (MIT), Simple Icons (CC0). Brand marks from Simple Icons are trademarks of their respective owners — use them per each brand's guidelines.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选