CardWorthScanner — TCG Price, Centering & PSA Grading ROI Engine
Calculate PSA/BGS/CGC card grading ROI, 55/45 centering grades & Pokemon/Yu-Gi-Oh market values.
作者提供的说明(英文原文)
Film stills from 5,489 films, searchable by lighting, lens character, shot size, colour and mood.
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。
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://framethrower.ai/api/mcp在终端中运行这条命令
claude mcp add --transport http framethrower https://framethrower.ai/api/mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"framethrower": {
"url": "https://framethrower.ai/api/mcp"
}
}
}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": {
"framethrower": {
"type": "http",
"url": "https://framethrower.ai/api/mcp"
}
}
}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://framethrower.ai/api/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。
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。
我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。
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8日
注册名称已通过域名 framethrower.ai 验证(注册中心会核实域名所有权)
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
尚未检查;我们会轮流检查各个端点
尚未检查;我们会轮流检查各个端点
尚未检查;我们会在检查端点时读取工具列表
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 1 项适用的基础检查中通过了 1 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。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。
GitHub 仓库最后更新于–,最新版本(1.0.0)于3个月前进入注册中心。
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:CardWorthScanner — TCG Price, Centering & PSA Grading ROI Engine, Sports MCP Server, Social Content 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
Calculate PSA/BGS/CGC card grading ROI, 55/45 centering grades & Pokemon/Yu-Gi-Oh market values.
NBA, NFL, NHL and combined sports scores as agent tools.
Steam games, Dev.to articles, events and podcasts as agent tools.
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。
Film references, inside your agent. Connect any MCP client to a cinematography reference library of 5,489 films, indexed frame by frame on lighting, lens character, shot size, colour and mood.
Ask for a look in conversation and the agent comes back with real frames, credited to their film, director and cinematographer.
https://framethrower.ai/api/mcp
Remote server, OAuth 2.1, four tools, no rate limits, $2 of credits free on signup (no card).
Settings → Connectors → Add custom connector → paste:
https://framethrower.ai/api/mcp
Sign in when the browser opens. That's it.
One-click:
Or add to ~/.cursor/mcp.json:
{
"mcpServers": { "framethrower": { "url": "https://framethrower.ai/api/mcp" } } }
Bridge with mcp-remote, which handles the OAuth flow for you:
{
"mcpServers": { "framethrower": { "command": "npx", "args": ["-y", "mcp-remote", "https://framethrower.ai/api/mcp"] } } }
Full per-client steps in docs/install.md.
| Tool | Credits | What it does |
|---|---|---|
search_frames | 2 | Search by concept, mood, colour, composition or scene, in natural language |
find_by_craft | 2 | Find frames by cinematography attribute — lens, shot size, style, setting, time of day, director, year |
find_similar | 2 | More frames like one already shortlisted. This is the refinement loop |
get_frame_details | 2 | Full metadata, thumbnail and link for a single frame |
search_frames| Argument | Type | Notes |
|---|---|---|
query | string, required | e.g. "neon-lit rainy street at night" |
limit | number, 1–40 | defaults to 12 |
find_by_craftAll optional — combine them to narrow.
| Argument | Type | Notes |
|---|---|---|
lens | string | "anamorphic", "spherical", "vintage_soft" |
shot_size | string | "closeup", "wide", "medium" |
visual_style | string | |
setting | string | "interior" or "exterior" |
time_of_day | string | "night", "day" |
director | string | |
year_min / year_max | number | year range |
limit | number, 1–40 | defaults to 12 |
find_similar| Argument | Type | Notes |
|---|---|---|
frameId | string, required | an id from a previous result |
limit | number, 1–40 | defaults to 12 |
get_frame_details| Argument | Type | Notes |
|---|---|---|
frameId | string, required |
The server sends usage instructions on connect, so a client doesn't need to be told how to behave. The loop it asks for:
search_frames with what you described.find_similar on that frame, or a find_by_craft with attributes adjusted.Every result keeps a link back to FrameThrower, because inline image rendering in chat is unreliable and the gallery is where the frames look like themselves.
See examples/prompts.md for conversations that work.
$2 of credits free on signup, no card. Then $1 = 1,000 credits, and each tool call costs 2 — so $1 covers 500 calls. Credits never expire. There are no rate limits.
Run out and the tool replies with a message saying so, including your balance and where to top up, so the agent can explain itself rather than failing silently.
Tools return metadata, a thumbnail URL, colour palettes and a deep link back to FrameThrower. Never raw image bytes.
This is a discovery and reference tool, not an image-delivery pipe. The frames are not ours to license — they are shown at reduced resolution as references for commentary, education and study, and rights remain with their owners. See intended use.
The FrameThrower MCP server is remote and hosted — you connect to it, you don't run it. So this repo is the connector: manifests, per-client setup, tool signatures and worked examples. Nothing to install, nothing to keep running, and no API key to manage — OAuth means the agent acts as your signed-in FrameThrower account.
npm install framethrower-ai (source)Same account, same credits.
FrameThrower is the reference app for the future creative: one of the largest film still libraries on the internet, callable from a REST API, an MCP server and an npm SDK. Built by senior filmmakers and ads creatives, for working film professionals.
MIT licensed.