Z
zhuyansen/new-term-radar
New model and product names before keyword tools
在 GitHub 查看 ↗链接已于 2026-11-12 核查 · HTTP 200 · 打开的是厂商自己的官网
安装与配置
- 复制上面的命令
- 粘成
claude_desktop_config.json里mcpServers的一项（本地服务器用 command + args，示例见 客户端接法） - 重启客户端
客户端配置（取自该仓库的安装命令）
{
"mcpServers": {
"zhuyansen-new-term-radar": {
"command": "uvx",
"args": ["new-term-radar"]
}
}
}解析自我们于 2026-11-04 抓取的该仓库 README；我们未执行过。
command/args 来自仓库写明的安装命令；不确定时请以该项目 README 为准。
VS Code（.vscode/mcp.json —— 键名是 servers）
{
"servers": {
"zhuyansen-new-term-radar": {
"command": "uvx",
"args": ["new-term-radar"]
}
}
}VS Code 顶层键是 <code>servers</code>，其余与上面那份相同。
Claude Code（命令行）
claude mcp add --transport stdio zhuyansen-new-term-radar -- uvx new-term-radar
Claude Code 不收 JSON 文件，用这条命令直接加。
配置项的键名以你的客户端为准：客户端与 CLI
- 来源明细
- 收录自 abordage/awesome-mcp 榜单（我们从中收集的条目之一） · 条目类型：MCP 服务
- 收录与活跃
- 收录于 2026-11-05 · 最近见到 2026-11-14 · 共见到 10 次 · 被 10 个来源列出
- 评分构成
- 综合分 1,003 · 10 个来源 · mcp
- 安装
uvx new-term-radar
常见问题（答案都来自我们的记录）
怎么安装？
该仓库给出的安装命令是
uvx new-term-radar。我们的记录里它是仓库自己提供的；不保证在你的客户端上直接可用。它适合谁 / 用来做什么？
我们把它归在这些标签下: MCP 服务。标签来自条目自身，不是我们强加的分类。
谁维护它、还在更新吗？
我们收录于 2026-11-05；最近见到 2026-11-14。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
# new-term-radar
以下摘录自该仓库的 README（片段） · 在 GitHub 读完整 README →
Catch the names AI people are about to search for, the day they appear, before keyword tools list them.
⭐ 700+ stars on its first day, 1,000 in just over three · on PyPI, the official MCP Registry, Cursor Directory, LobeHub, Tessl, ClawHub and skills.sh
Quick start · What it reads · The keyword table · Agents and MCP · config.json · 中文说明
A daily report of the names that are starting to surge in AI: new models, products, tools and repos, caught where they are said first, before they show up in keyword tools.
Built for people who make pages, posts or products around new terms: SEO for AI tool sites, newsletters, directories, anyone who wants to know about "Strata" or "Seedance" the day it appears and not two weeks later.
## Why
A new name leaves a trail, in this order:
1. A lab or a well-followed account says it on X; a model enters Hugging Face's trending list.
2. One GitHub repo takes off on its own.
3. Directories and competitors add pages for it; someone registers a domain for it and the site starts to rank.
4. Your own site gets its first search impressions for it.
5. Google Trends shows the curve, days or weeks later.
Keyword tools read step 5. This radar reads steps 1 to 4 every day and uses step 5 only to check itself.
One example it was built around: Niko1221/Strata was created on 2026-09-24 and had 7,700 stars nine days later. People were searching "niko strata" from 9/26, while no second repo carried the name and no keyword tool listed it. A single repo gaining 800 stars a day is the whole signal, and it is public.
## What it reads
Purple, tagged NEW: what 0.6.0 added. On the keyword table: word age, markets, page-one shape, the twelve months, your own rank, what else holds page one (threads, an AI overview) and the exact-match .com. The first words ③'s new sites rank for, what ChatGPT recommends for ⑦'s asks, three more payment platforms and the builders on ⑧, ⑨ just listed, ⑩ money and the evidence beside the names. All of it is in CHANGELOG.md.
| Signal | What it catches | Needs | Cost |
| ① X | Names the accounts in your list used for the first time in 60 days | AIsa key | $0.003 per account per run |
| ① Hugging Face | Models and Spaces (the demos people try) new to the trending top 50; quantised copies and a model's own demo grouped under the base name | nothing | free |
| ② GitHub breakout | A repo under 14 days old averaging 200+ stars a day, or +400 since yesterday; adds the search variants people use ("niko strata") | nothing (a GitHub token raises the rate limit) | free |
| ③ Sitemaps | Words that several new URLs on a site share and its older URLs rarely carried. The example config watches eight AI tool directories (toolify, aixploria, ai-bot.cn, opentools, dang.ai, clipfly, aitoptools, futurepedia) and four MCP and skill directories | the sitemaps you list | free |
| ③ New sites | Domains registered and first indexed in the last 90 days that already rank for 20+ keywords, each new one with the first words it ranks for in Google's top 20, in any country: searches a site that new already reached | AIsa key | about $0.13 per query, weekly; about $0.013 a new site for its words |
⭐ 700+ stars on its first day, 1,000 in just over three · on PyPI, the official MCP Registry, Cursor Directory, LobeHub, Tessl, ClawHub and skills.sh
Quick start · What it reads · The keyword table · Agents and MCP · config.json · 中文说明
A daily report of the names that are starting to surge in AI: new models, products, tools and repos, caught where they are said first, before they show up in keyword tools.
Built for people who make pages, posts or products around new terms: SEO for AI tool sites, newsletters, directories, anyone who wants to know about "Strata" or "Seedance" the day it appears and not two weeks later.
## Why
A new name leaves a trail, in this order:
1. A lab or a well-followed account says it on X; a model enters Hugging Face's trending list.
2. One GitHub repo takes off on its own.
3. Directories and competitors add pages for it; someone registers a domain for it and the site starts to rank.
4. Your own site gets its first search impressions for it.
5. Google Trends shows the curve, days or weeks later.
Keyword tools read step 5. This radar reads steps 1 to 4 every day and uses step 5 only to check itself.
One example it was built around: Niko1221/Strata was created on 2026-09-24 and had 7,700 stars nine days later. People were searching "niko strata" from 9/26, while no second repo carried the name and no keyword tool listed it. A single repo gaining 800 stars a day is the whole signal, and it is public.
## What it reads
Purple, tagged NEW: what 0.6.0 added. On the keyword table: word age, markets, page-one shape, the twelve months, your own rank, what else holds page one (threads, an AI overview) and the exact-match .com. The first words ③'s new sites rank for, what ChatGPT recommends for ⑦'s asks, three more payment platforms and the builders on ⑧, ⑨ just listed, ⑩ money and the evidence beside the names. All of it is in CHANGELOG.md.
| Signal | What it catches | Needs | Cost |
| ① X | Names the accounts in your list used for the first time in 60 days | AIsa key | $0.003 per account per run |
| ① Hugging Face | Models and Spaces (the demos people try) new to the trending top 50; quantised copies and a model's own demo grouped under the base name | nothing | free |
| ② GitHub breakout | A repo under 14 days old averaging 200+ stars a day, or +400 since yesterday; adds the search variants people use ("niko strata") | nothing (a GitHub token raises the rate limit) | free |
| ③ Sitemaps | Words that several new URLs on a site share and its older URLs rarely carried. The example config watches eight AI tool directories (toolify, aixploria, ai-bot.cn, opentools, dang.ai, clipfly, aitoptools, futurepedia) and four MCP and skill directories | the sitemaps you list | free |
| ③ New sites | Domains registered and first indexed in the last 90 days that already rank for 20+ keywords, each new one with the first words it ranks for in Google's top 20, in any country: searches a site that new already reached | AIsa key | about $0.13 per query, weekly; about $0.013 a new site for its words |
收录徽章（可选）
想把收录标记放进 README 就复制这行，可选，不影响收录。
[](https://anclum.com/zh/s/zhuyansen-new-term-radar/)
- 来源
- awesome · https://github.com/zhuyansen/new-term-radar
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