Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
作者提供的说明(英文原文)
Search 14.5M Smithsonian Open Access objects, get CC0 images, find cross-collection connections.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
SMITHSONIAN_API_KEY, MCP_LOG_LEVEL你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
适用于网页版、桌面版和手机版 Claude:
https://smithsonian.caseyjhand.com/mcp打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"smithsonian": {
"command": "npx",
"args": [
"-y",
"@cyanheads/smithsonian-mcp-server"
],
"env": {
"SMITHSONIAN_API_KEY": "your-value",
"MCP_LOG_LEVEL": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add --transport http smithsonian https://smithsonian.caseyjhand.com/mcpclaude mcp add smithsonian --env SMITHSONIAN_API_KEY=your-value --env MCP_LOG_LEVEL=your-value -- npx -y @cyanheads/smithsonian-mcp-server运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"smithsonian": {
"url": "https://smithsonian.caseyjhand.com/mcp"
}
}
}粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"smithsonian": {
"command": "npx",
"args": [
"-y",
"@cyanheads/smithsonian-mcp-server"
],
"env": {
"SMITHSONIAN_API_KEY": "your-value",
"MCP_LOG_LEVEL": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"smithsonian": {
"type": "http",
"url": "https://smithsonian.caseyjhand.com/mcp"
}
}
}粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"smithsonian": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@cyanheads/smithsonian-mcp-server"
],
"env": {
"SMITHSONIAN_API_KEY": "your-value",
"MCP_LOG_LEVEL": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
ChatGPT 只能连接互联网上的服务器:
https://smithsonian.caseyjhand.com/mcp菜单名称可能因套餐和版本不同而略有差异。
你的选择通过 Cookie 保存在这台设备上,无需账户。
MCP_LOG_LEVEL env这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
工具名称和描述与服务器在 2026年11月6日 报告的完全一致。这些内容由作者撰写,不是我们写的;我们以纯文本形式显示。
smithsonian_search_objectsRecommended first step for open-ended or topic discovery: free-text search across 14.5 million Smithsonian objects, with optional exact filters. Filters narrow by museum unit, object type, indexed date term, culture, geographic place, subject topic, named party, and online/CC0 av
smithsonian_list_termsEnumerate the valid term vocabulary for an indexed Smithsonian filter field (unit_code, culture, place, date, online_media_type, topic). Terms are a controlled vocabulary — often plural or qualified (e.g. "Paintings", not "Painting") — so guessed filter values tend to return noth
smithsonian_get_objectFetch a normalized catalog metadata projection for a Smithsonian object by its record_id (from smithsonian_search_objects results). Returns title, dates, description, labeled notes, makers, materials, dimensions, places, cultures, topics, exhibitions, credit line, identifiers, ri
smithsonian_get_mediaReturn every CC0 (open-access) image for a Smithsonian object at multiple resolutions. The tool never returns an empty list — it names the reason instead: an object with nothing digitized, an object whose media is entirely non-image (3D models, scanned books, documents), and an o
smithsonian_browse_categoryBrowse Smithsonian objects within one exact category — a single museum (mode "museum"), culture, indexed date term (mode "period"), object type (mode "medium"), or subject term (mode "topic"). The value must be an exact indexed category term, not free text: resolve museum, cultur
smithsonian_find_relatedDiscover objects across Smithsonian collections related to a given anchor object, matched on shared metadata signals — culture, period, object type, named parties, and topic terms. Each related object is tagged with the signals that connected it to the anchor; a named-party signa
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过 GitHub 账户 cyanheads 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
在 133 毫秒内响应(HTTP 200)
无需登录
已读取 6 个工具描述,未发现针对 AI 的隐藏指令
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 3 项适用的基础检查中通过了 3 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
你需要填写:SMITHSONIAN_API_KEY
两种方式都可以:安装在你的电脑上,或者连接云端版本。
GitHub 仓库最后更新于–,最新版本(0.4.0)于6天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
同一分类中有:Figma Context MCP, Claude Real Video, Figma MCP Server
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
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.
The Figma MCP server brings Figma design context directly into your AI workflow.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
@cyanheads/smithsonian-mcp-server Search 14.5M Smithsonian Open Access objects across 20+ museums via MCP, and retrieve CC0 images for the 5.2M that carry openly-licensed media. STDIO or Streamable HTTP. 6 Tools
Public Hosted Server: https://smithsonian.caseyjhand.com/mcp
The Smithsonian's Open Access catalog: 14.5 million objects across 20+ museums, 5.2 million with CC0 images. Search by free text or category, browse by museum, culture, date, or topic, and discover connections across collections.
| Tool | Description |
|---|---|
smithsonian_search_objects | Search across 14.5M objects by text query with optional filters (museum, type, date term, culture, place, topic, name, scientific name, media type, online-only, CC0). Returns curated summaries with total count. |
smithsonian_list_terms | Enumerate the valid term vocabulary for an indexed filter field (unit_code, culture, place, date, online_media_type, topic). Call before filtering to avoid empty results from invalid values; pass contains to resolve a guessed value to its exact term(s). unit_code terms come back with their museum names. |
smithsonian_get_object | Fetch a normalized catalog metadata projection for an object by ID: title, dates, materials, dimensions, exhibition history, credit line, and identifiers. |
smithsonian_get_media | Return all CC0-licensed images for an object at multiple resolutions (thumbnail, screen, high-res JPEG/TIFF). Only CC0 images returned, never an empty list — a distinct error reason names why, whether the object has nothing digitized, only non-image media, or only restricted images. |
smithsonian_browse_category | Browse objects within one exact category (museum, culture, period, medium, topic) with total count, a page of objects, and museum breakdown. Requires an exact indexed category term. |
smithsonian_find_related | Discover cross-collection objects related to an anchor, matched on shared culture, named-party, topic, and period signals. |
| Skill | Description |
|---|---|
smithsonian-guide | Gates for agents querying the catalog: query syntax (OR never widens a search), counting a museum's or a place's holdings, finding a person's indexed name, genus-level scientific names, and mirror-served pages |
Ships in skills/ for plugin installs, the npm package, the Docker image, and the .mcpb bundle, and is served over MCP as skill://smithsonian-guide/SKILL.md.
smithsonian_search_objects toolAND constraints. Plain words and quoted phrases keep their matching semantics; active Lucene expressions are grouped to preserve Boolean precedence.filters.online_media_type accepts exact smithsonian_list_terms media categories such as Images, 3D Models, and Sound recordings. These describe the index; even Images does not guarantee attached or CC0 images. Check smithsonian_get_object.media_summary for deliverability. Media categories feed search, with no media-type browse mode.1920s, 500-1500, 21st century, -2500), culture, geographic place, subject topic, named party (name), scientific name (scientific_name), indexed media category (online_media_type), online-only, CC0-onlytopic and name are hard indexed constraints, not free text — topic: "Quilts" matches 1,134 objects where the bare word matches 2,677, and name: "Warhol, Andy" matches 421 against 715record_id, plus holding_museum_name when the holding unit differs from the indexed unit_code (the 3D digitization scans)filters key is rejected by namestart + rows for standard pagination (offset-based, default 20, up to 1,000 per page — a larger rows is served at 1,000 with a notice). When objects remain, the notice names the next startsmithsonian_list_terms toolunit_code, culture, place, date, online_media_type, topic — a controlled vocabulary, often plural (e.g. Paintings, not Painting); ground filter values here before searching or browsingcontains filters the vocabulary by a case-insensitive substring — resolves a guessed value (e.g. greek → Greek, Attic) in one call; for unit_code it also matches museum names (National Air and Space → NASM), and each unit_code term comes back with a labels map of its museum namestart + rows (default 50, up to 40,000 per page — a larger rows is served at 40,000 with a notice); topic (133k terms) and place (114k) are large enough to pair with containsSMITHSONIAN_TERMS_CACHE_TTL_SECONDS (default 3600 seconds, 0 disables) — upstream ignores paging and returns the whole set on every call, so paging a large vocabulary uncached re-downloads it each timeobject_type is not enumerable here — harvest its values from the object_type field in smithsonian_search_objects resultssmithsonian_get_object toolrecord_id from smithsonian_search_objects — do not construct IDs manuallysmithsonian_get_media for full image URLs. media_summary.non_image_media[] lists every media item that is not an image (3D models, scanned books, documents) as { type, url?, is_cc0 }, in catalog orderholding_museum_name names the holding unit when it differs from unit_code, the code the record is indexed under (the 3D digitization scans); the text output renders it as Held bydescription selects recognized prose labels; administrative notes stay labeled.scientific_names, reported taxonomy ranks, and valid decimal collection coordinates with their own locality when present. The arrays are empty when no names or valid points are available; absent ranks are omitted. No accepted name, geocoding, or accuracy is inferred. Use scientific_names as exact filters.scientific_name values in search; this field is not enumerable via smithsonian_list_terms.smithsonian_get_media toolno_media (nothing digitized), no_images (media exists but is entirely non-image — 3D models, scanned books, documents; the recovery hint names the types present and points to smithsonian_get_object's media_summary.non_image_media, which links each item), not_cc0 (images exist but none are CC0, thrown as Forbidden)smithsonian_search_objects with filters.cc0_only: true to find objects with downloadable CC0 images before calling this toolsmithsonian_browse_category toolmuseum (by unit code, e.g. "NASM" — matched exactly, not by museum name), culture (e.g. "Aztecs"), period (indexed date term, e.g. "1940s" or "500-1500"), medium (object type, e.g. "Paintings"), topic (subject term, e.g. "Quilts")value must be an exact indexed category term — resolve museum, culture, period, and topic vocabulary with smithsonian_list_terms first; object_type is not enumerable there, so harvest it from smithsonian_search_objects resultsstart + rows for standard pagination (offset-based, default 10, up to 1,000 per page — a larger rows is served at 1,000 with a notice). When objects remain, the notice names the next start — adjacent pages retrieve the objects a capped sample omitsinvalid_category with a mode-specific recovery hint: a value outside the vocabulary gets the exact smithsonian_list_terms call that resolves it, and a value the index enumerates but that matches no objects is named as such and routed elsewheresmithsonian_search_objects instead — this tool requires an exact category valuesmithsonian_find_related toolmaker, collector, donor, issuing authority, …) rather than a fixed maker label, prefers the indexed name facet as a hard filter when the record has one, and is dropped when its value only repeats the culture signaltopic: filter, so every object it tags carries that subject term rather than merely mentioning the wordsimilarity_signals on each result names every metadata term that conne只显示了开头部分;其余内容请在仓库中阅读