citation-intelligence-mcp

A free, self-hosted MCP server that tells your agent what LLMs cite - across Perplexity, Google AI Overviews, ChatGPT, Claude, Gemini, and Bing.

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What it can do

  • Citations.Check: Return URLs cited by an AI engine (Perplexity, Claude, ChatGPT, Gemini, or Bing) for a query. Use this when an agent or user wants to see what sources an AI search engine grounds answ
  • Domain.Am I Cited: Check whether a domain is cited by an AI engine across a cluster of queries. Returns per-query presence, rank, and a citation-rate summary. Use to measure visibility for a brand, pr
  • Signals.Ai Overview: Check whether Google shows an AI Overview for a query, and which URLs it cites. Uses SerpAPI (free tier: 100/month). Set SERPAPI_KEY.

What data it sees

Do you need an account

No: the server works without sign-in

A free, self-hosted MCP server that tells your agent what LLMs cite - across Perplexity, Google AI Overviews, ChatGPT, Claude, Gemini, and Bing.

How to connect

How to connect citation-intelligence-mcp to Claude

The server address to paste into Claude settings:

https://citation-intelligence-mcp--automatelab.run.tools

  1. Open Claude (claude.ai or the desktop app).
  2. Go to Settings → Connectors.
  3. Click Add custom connector.
  4. Paste the server address copied below into Remote MCP server URL and click Add.
  5. In a chat, click + → Connectors and switch the new connector on.

Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

Authorization

After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

How to connect citation-intelligence-mcp to ChatGPT

The server address to paste into ChatGPT settings:

https://citation-intelligence-mcp--automatelab.run.tools

  1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
  2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
  3. Open Settings → Connectors and click Create.
  4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
  5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
  6. In a new chat open + → Apps/Connectors and enable the connector.

OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

Authorization

On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

How to connect citation-intelligence-mcp to Cursor

The server address to paste into Cursor settings:

https://citation-intelligence-mcp--automatelab.run.tools

Fastest: click Open in Cursor below and confirm the prompt.

Manually:

  1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
  2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
  3. Save the file. The server appears in the MCP list; authorize it there if asked.

Authorization

If the service needs sign-in, an authorize button appears next to the server in the MCP list.

Server tool list (24)

Raw names from tools/list. Only developers need these.

citations.checkReturn URLs cited by an AI engine (Perplexity, Claude, ChatGPT, Gemini, or Bing) for a query. Use this when an agent or user wants to see what sources an AI search engine grounds answers on. Requires at least one engine API key; auto-picks the first available.
domain.am_i_citedCheck whether a domain is cited by an AI engine across a cluster of queries. Returns per-query presence, rank, and a citation-rate summary. Use to measure visibility for a brand, product, or content site in AI search.
signals.ai_overviewCheck whether Google shows an AI Overview for a query, and which URLs it cites. Uses SerpAPI (free tier: 100/month). Set SERPAPI_KEY.
domain.cited_forList queries that the given domain has been cited for, served from the local cache. Build up a corpus by calling check_citations or am_i_cited first; cited_for queries it without spending API budget.
citations.predictScore citation likelihood for a URL from public signals (Wikipedia link presence, schema.org markup, /llms.txt, GitHub and Reddit references, canonical hygiene, HTTPS). No LLM fired - all heuristic. Returns 0-100 score, grade, signal breakdown, and ranked fixes.
panel.trackSave, load, or list named query panels. A panel is a persisted set of queries you want to monitor over time (e.g. editorial-watchlist). Use action=save with queries[] to create, action=load to read, action=list to enumerate. Panels live under <config>/panels/<name>.json.
panel.runRun a saved panel through am_i_cited and append a timestamped snapshot. Snapshots live under <config>/snapshots/<panel>/<iso>.json. Feeds citation_trend.
citations.trendReport citation rate over time for a panel from stored snapshots. Returns the series of citation_rate per snapshot plus per-query deltas (gained/lost/unchanged) between first and last snapshot.
competitors.compareRun predict_citation on 2-10 URLs and return a side-by-side signal table plus a list of signals where the URLs diverge. Use to compare your URL to top-cited competitors for the same query.
signals.wikipediaList Wikipedia articles that reference the given domain. Wikipedia citation is the highest-lift signal for LLM training corpora. Zero keys required.
audit.sitemapFetch a sitemap.xml (or sitemap index) and run predict_citation on every URL. Returns results sorted worst-score-first. Surfaces systemic issues across a whole site in one pass. Zero engine keys needed.
competitors.competeEnd-to-end competitive snapshot for a single query. Calls check_citations to get the cited URLs, then runs compare_domains on your_url vs the top cited competitors. Returns your score, the average competitor score, and the gap.
citations.freshnessScore how recent the pages cited for a query are. Calls check_citations, then collects dateModified for each cited URL, returns a 0-100 recency_score (halflife=365d) plus per-URL freshness bucket (fresh/current/stale/ancient/unknown). Surfaces queries where AI cites old content - opportunity to ship fresher.
domain.cited_for_diffDiff cited_for between two time windows for a domain. Returns queries gained (cited now, not before baseline_until) and queries lost (cited before, not since current_since). Cache-only, no API spend. Use to track citation drift over time after publishing or migrating content.
signals.gsc_gapJoin Google Search Console performance with am_i_cited per query. Surfaces queries where the domain ranks well in Google but is not cited in AI - the closest editorial wins. Requires GCP service account creds (credentials_path or GOOGLE_APPLICATION_CREDENTIALS env).
audit.schemaDeep schema.org validation for a URL. Parses every JSON-LD block and microdata node, checks required fields per @type (Article needs headline+author+datePublished, FAQPage needs mainEntity, HowTo needs step, etc.), and flags missing fields and malformed JSON-LD. Returns issues list and a valid/invalid verdict. Use to fix structured-data bugs that predict_citation flags but can't explain.
audit.llms_txtGenerate an llms.txt file (https://llmstxt.org spec) from a sitemap. Parses sitemap.xml + nested indexes, groups URLs by top-level path, and emits a Markdown document with H1+description+sectioned link lists. Set fetch_titles=true to pull <title> per URL (slower, richer output).
signals.answer_boxLocate where each cited URL appears in the AI's raw answer text. Calls check_citations, finds the first mention of each citation's URL (or hostname) in raw_answer, and bins by char position into early/middle/late thirds. Surfaces whether your URL is cited up-front or buried near the end. Returns 'unknown' for engines without raw_answer (Bing, Brave).
citations.provenanceFan a query out across multiple AI engines and report per-URL cross-engine consensus. Returns each unique cited URL with the list of engines that cited it, plus a consensus_urls list (URLs cited by ALL engines). High engine_count = strong cross-engine citation signal; engine_count=1 = engine-specific.
citations.evidenceExtract the cited snippet from the AI engine's raw answer for each citation. Calls check_citations, then for each returned URL finds the first mention in raw_answer and returns a context window plus the nearest quoted span or containing sentence. Use to see *why* an engine cited a URL, not just *that* it did. Returns 'not found' for engines without raw_answer (Bing, Brave).
audit.crawler_accessVerify that major AI crawlers (GPTBot, OAI-SearchBot, ClaudeBot, PerplexityBot, CCBot, Google-Extended, Applebot-Extended, Bytespider, Meta-ExternalAgent, plus real-time fetch UAs) can fetch a URL. Parses robots.txt and does a live GET with each bot's User-Agent. Surfaces robots.txt blocks AND UA-based gating that breaks AI citation.
audit.sitemap_mapCross-reference a sitemap with the citation cache. For each sitemap URL, reports whether it appears in cached citations (and how many queries/engines cited it). Inverse of audit_sitemap: not 'how citable is each URL', but 'has each URL actually been cited yet'. Cache must be primed via check_citations or run_panel first.
competitors.canonical_setFan a query across engines and aggregate citations by registered domain (not URL). Returns top competitor domains ranked by cross-engine consensus, with per-engine breakdown and top URLs per domain. Use to identify the canonical competitor set for a query - the domains every engine treats as authoritative.
audit.structured_dataSuggest missing JSON-LD additions for a URL. Fetches the page, detects existing schema types, and returns ready-to-paste templates for types that are missing but signalled by page content (BlogPosting from og:type=article or bylines, FAQPage from Q&A pairs, HowTo from numbered steps, BreadcrumbList from nested paths, Organization on homepages). Templates are pre-filled from page metadata where possible; fields marked FILL: require manual completion.