原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
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citable

作者:genzagents版本 0.4.2i★ –i在你的电脑上运行
注册名称io.github.genzagents/citable

安装

概览

作者提供的说明(英文原文)

Can ChatGPT, Claude and Perplexity read and cite your site? robots.txt, edge blocks, llms.txt.

PopNx MCP 的三大支柱

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。

它能帮你做什么

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。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 搜索与 AI 记忆

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

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 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "citable": {
      "command": "uvx",
      "args": [
        "citable-cli",
        "mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add citable -- uvx citable-cli mcp

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "citable": {
      "command": "uvx",
      "args": [
        "citable-cli",
        "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。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "citable": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "citable-cli",
        "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。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

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。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

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6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 genzagents 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“搜索与 AI 记忆”中的其他服务器比较i

  • 星标数多于此分类中其他 7240 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 7240 个服务器的 80% 更新
  • 基础检查结果等于或优于此分类中其他 7240 个服务器的 100%

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。

常见问题

citable 安全吗?

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。

它需要哪些密钥或代码?

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。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.4.2)于9天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。

有什么可以替代它?

同一分类中有:Context7, Codebase Memory, Exa

替代选择

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

Context7

作者:upstash

Up-to-date docs for AI agents

电脑或云端★ 64,224MIT3天前更新
安装

Codebase Memory

作者:DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

在你的电脑上运行★ 48,148MIT20天前更新
安装

Exa

作者:exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

在云端运行★ 5,213MIT44天前更新
安装

作者的 README

打开 README

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。

citable

Can ChatGPT, Claude and Perplexity actually read and cite your site?

Most "AI visibility" checkers read robots.txt and stop. citable fetches your homepage as each AI bot and reports the blocks that robots.txt never mentions (Cloudflare "Block AI bots", WAF rules, rate limiters), then checks the rest of the list: llms.txt, JSON-LD, title and description, JS-only content, sitemap, canonical. Score out of 100, every failure with the fix. Also runs as an MCP server so your agent can check sites for you.

Zero dependencies. One file. Python 3.9+.

pipx install citable-cli     # from PyPI; on a Mac: brew install pipx first. Or: uvx --from citable-cli citable

citable example.com # report citable example.com --json # for scripts and CI (exit 1 if below --min-score=N) citable example.com --llms-txt # a starter llms.txt built from your homepage citable watch a.com b.com # weekly watch: GitHub issue per site, comment (email) on regressions citable track a.com "best X" "how Y" # prompt tracking: which engines cite you, who gets cited instead

No install at all:

curl -sL https://raw.githubusercontent.com/genzagents/citable/main/citable/__init__.py | python3 - example.com

What a run looks like

citable 0.3.0: https://reddit.com/

score 13/100 grade F (final URL https://www.reddit.com/)

[FAIL] 0/15 robots.txt allows answer engines: robots.txt blocks: OAI-SearchBot, ChatGPT-User, Claude-SearchBot, ... [FAIL] 0/20 Answer engines not blocked at the edge: Fetching the homepage as a bot: ChatGPT-User got HTTP 403; a browser got 200. fix: Your CDN or WAF (Cloudflare 'Block AI bots', bot-fight mode, a rate limiter) is refusing them ... [FAIL] 0/15 /llms.txt: /llms.txt returns HTTP 404. ... Bot Vendor Role robots.txt live fetch OAI-SearchBot OpenAI answer block HTTP 200 ChatGPT-User OpenAI answer block HTTP 403 <- BLOCKED Claude-SearchBot Anthropic answer block HTTP 200 ...

What it checks

CheckPointsWhy it matters
robots.txt allows the answer bots (OAI-SearchBot, ChatGPT-User, Claude-SearchBot, Claude-User, PerplexityBot, Perplexity-User, DuckAssistBot, Bingbot, Googlebot)15These fetch pages to answer live questions and cite the source. Blocked means never cited.
Not blocked at the edge: homepage fetched as each of those bots returns what a browser gets20CDN and WAF "block AI" toggles stop bots that robots.txt allows. Nothing else on this list matters until this passes.
Training crawlers (GPTBot, ClaudeBot, Google-Extended, CCBot, Applebot-Extended, meta-externalagent, Amazonbot, Bytespider)infoBlocking them is a legitimate choice and does not affect citations. Reported, never penalised.
/llms.txt present, plain text, with an H1, a > summary and links15The convention answer engines and agents read first. A soft-404 HTML page counts as missing.
Content readable without JavaScript (words in the raw HTML)15Most AI crawlers do not run JS. A client-rendered shell is invisible to them.
JSON-LD structured data (Organization, WebSite, Article, FAQPage...)10Entities and FAQs get quoted directly.
Title and meta description, sensible lengths8Quoted verbatim in answers.
HTTPS, response time, canonical, Open Graph, sitemap, , no noindex22Hygiene that decides which URL gets the citation.

As an MCP server (Claude Code, Claude Desktop, Cursor, any MCP client)

Tools: check_site(url, live=true) and draft_llms_txt(url).

Claude Code plugin (includes the MCP server and a skill that knows how to act on the report):

claude plugin marketplace add genzagents/marketplace

claude plugin install citable@genzagents

Any MCP client, by hand:

{ "mcpServers": { "citable": { "command": "python3", "args": ["/path/to/citable/citable/__init__.py", "mcp"] } } }

The server speaks MCP over stdio with no dependencies, so it runs anywhere Python does.

In CI

Fail the build when a deploy breaks AI access (a new WAF rule, a lost llms.txt, a Disallow: / that slipped in):

citable yoursite.com --min-score=70 --json > citable.json

Watch

A deploy that flips a WAF toggle silently removes you from every AI answer. The watch is the alarm. It runs as a GitHub Action in any repo you own (it need not be the site's repo), keeps one issue per site up to date, and comments on that issue the moment an answer bot is blocked, `llms.txt` disappears, the site goes down or the score drops, which GitHub emails to you. No server, no account, no dependencies. Example: issue #1 watches this project's own page.

Copy docs/watch.yml to .github/workflows/citable-watch.yml:

on:

schedule: [{ cron: "17 6 * * 1" }] # Mondays workflow_dispatch: permissions: { issues: write, contents: read } jobs: watch: runs-on: ubuntu-latest steps:

  • uses: genzagents/citable@v0.4.2 with: sites: | example.com docs.example.com

min-score: 75

Inputs: sites (required), min-score (fail below it), live (fetch as each bot, default true), issue (track in an issue, default true), notify (login to @mention on a regression, default repo owner), fail-on-regression (default true). Outputs: score, regressed, changed. Same thing from a shell where gh is logged in:

citable watch example.com docs.example.com --repo=you/your-repo --notify=you

Hosted, $12/month (about £9): the same watch run by us, no repo needed, up to 5 domains, with a weekly digest. Live now through GitHub Sponsors:

  1. Sponsor genzagents at $12 a month →
  2. Open your Hosted watch issue → from the same account. Reports are posted on it (the issue is public).

Track

The watch tells you whether engines *can* read you. Track tells you whether they *do*: for the questions you want to be the answer to, does ChatGPT, Claude or Perplexity link to your site, and who gets linked instead?

citable track example.com "best tools for X" "how do I Y" --brand=Example
## citable track: example.com

Visibility 50%: share of prompt-and-engine pairs where an answer linked to your site.

Promptanthropicopenaiperplexity
best tools for Xcitedmentionedcited
how do I Ynonono

Who gets cited instead (answers citing them): rival.io (4), other.org (2)

Engines: anthropic (ANTHROPIC_API_KEY, the web_search tool), openai (OPENAI_API_KEY, Responses API web search), perplexity (PERPLEXITY_API_KEY, sonar) and claude-code (the claude CLI on your machine, no key). Every engine whose key is present runs; --engines= picks a subset. Add --issue --repo=you/repo (or run it from the Action with a prompts: input) and it keeps a "citable track: example.com" issue up to date and comments when a citation is lost, which is the weekly email the paid tools charge $29 to $39 a month for. Bring your own keys; a 10-prompt run on three engines costs a few cents.

Hosted ($12/month, about £9)

No repo, no keys, no cron: sponsor genzagents at $12 a month, open a Hosted watch issue with your sites (up to 5), the prompts that matter (up to 10) and your brand, and the first report is posted on the issue within the hour. After that you get a comment the moment something regresses and a digest once a week with the prompt tracking (GitHub emails you each one). Cancel from your GitHub sponsorships page.

citable hosted run --source=github matches active sponsors to the open hosted issues they authored and comments the reports there, so it needs only a GitHub token. The Polar + Resend mode below is for private email delivery.

The runner is in this repo (citable hosted), so you can also run the same thing yourself for your own customers: it polls Polar for active subscriptions, keeps one small state file per subscriber, and sends through Resend. Zero dependencies, one hourly cron. See docs/HOSTED.md.

citable hosted run --dry-run                  # against Polar, prints the emails instead of sending

citable hosted run --subscribers=subs.json # against a local list (no Polar), e.g. for your own clients citable hosted launchd # a launchd plist that runs it hourly on a Mac

Notes

  • MCP registry name: mcp-name: io.github.genzagents/citable (PyPI package citable-cli; the import and the command stay citable).
  • Bot user agents and roles follow the vendors' published strings (OpenAI, Anthropic, Perplexity). Role "answer" = fetches to answer or cite in a live conversation; "train" = builds training corpora.
  • The edge check compares HTTP status only. A site that returns 200 with a challenge page to bots will pass; file an issue with the domain and it gets a heuristic.
  • --no-live skips the bot fetches (faster, robots.txt only).

Development

python3 -m unittest discover -s tests -v

MIT. Built by genzagents.

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