citable

Official registry AI and agents

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

Install

Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).

PYPI package citable-cli
Claude Code
claude mcp add citable -- uvx citable-cli==0.4.2 mcp
JSON configuration (Claude Desktop, Cursor, VS Code)
{
    "mcpServers": {
        "citable": {
            "command": "uvx",
            "args": [
                "citable-cli==0.4.2",
                "mcp"
            ]
        }
    }
}

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. citable
  2. What a run looks like
  3. What it checks
  4. As an MCP server (Claude Code, Claude Desktop, Cursor, any MCP client)
  5. In CI
  6. Watch
  7. Track
  8. Hosted (£9/month)
  9. Notes
  10. Development

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, <html lang>, 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, £9/month: the same watch run by us, no repo needed, up to 5 domains, with the weekly email. Not live yet; press the button to tell us you want it, that is what decides whether it gets built:

**I want the hosted weekly watch →**:%0A%0AWhat+would+you+pay+per+month%3F)

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.

| Prompt | anthropic | openai | perplexity |
|---|---|---|---|
| best tools for X | **cited** | mentioned | **cited** |
| how do I Y | no | no | no |

**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 (£9/month)

No repo, no keys, no cron: pay once a month, type your sites (up to 5), the prompts that matter (up to 10) and your brand at checkout, and the first report lands in your inbox within the hour. After that you get an email the moment something regresses and a digest once a week with the prompt tracking. Cancel from the receipt.

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.

Frequently asked questions

What is citable?

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

How do I install citable?

It runs on your machine. In Claude Code: claude mcp add citable -- uvx citable-cli==0.4.2 mcp. For other clients, paste the JSON configuration from this page into their MCP settings.

Does citable need an API key?

Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.

Is citable open source?

Yes. Its code is on GitHub under the MIT license.

Who maintains citable?

It is published by genzagents. AI.tn lists it but does not maintain or endorse it.

From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.