AutomateLab Citation Intelligence MCP

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.

What this is

An MCP server for agents and developers who need to know which URLs get cited by AI search engines for any query. Install once, query from any MCP-compatible client (Claude Desktop, Cursor, Claude Code, Continue, Cline, n8n, LangGraph). Self-hosted, no account, no centralized backend. Bring your own API keys; nothing is stored on a remote server.

Who this is for

Install this if you're:

• Building an agent that does research and want it to cite sources LLMs already trust
• A solo dev or indie hacker checking whether your SaaS is showing up in AI search
• A content creator confirming your articles are being cited by ChatGPT, Claude, or Perplexity
• An SEO or GEO practitioner who wants programmatic citation data without a $295-$499/mo dashboard
• Running an editorial pipeline and want citation-deficit-driven topic selection
• Comparing competitor visibility across AI engines for any niche

Do NOT install this if you want:

• A polished marketing dashboard with charts and team seats - try Profound, AthenaHQ, or Otterly.AI
• A hosted service with SLAs - this is self-hosted by design
• Citation tracking for academic papers - try citecheck
• 350M+ pre-modeled prompts - that's Ahrefs Brand Radar

Why this exists

The AI citation tracking market is dominated by VC-funded dashboards starting at $295/mo. None ships MCP-first. If you're an agent or developer who wants citation data piped directly into your workflow - not into a SaaS login - there isn't a tool for you. This is that tool.

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Tools

Tools are grouped into seven namespaces: citations_*, domain_*, signals_*, panel_*, report_*, competitors_*, audit_*. The prefix is the question category; the suffix is the action. Wire names use underscores (not dots) so Anthropic-API-based MCP clients (Claude Desktop, Claude Code) can forward the tool list without HTTP 400.

Start with citations_provenance or domain_am_i_cited. Single-engine results (citations_check with a pinned engine) are directional; multi-engine consensus is the honest signal. A URL cited by 4 of 5 engines is a very different finding than one cited by 1.

citations_* — query-level: who cites what, with what evidence

Tool	Purpose
citations_provenance	Recommended first tool. Fan a query across engines; per-URL cross-engine consensus matrix. Returns interpretation_note per engine.
citations_check	URLs cited by Perplexity / Claude / ChatGPT / Gemini / Google AI Mode for a query; or web rank via bing_serp / brave_serp
citations_evidence	Extract the cited snippet from raw_answer for each citation (why, not just that)
citations_predict	Citation likelihood from public signals - no LLM fired
citations_trend	Time-series report of citation rate + per-query gained/lost deltas
citations_freshness	Recency score (halflife=365d) for the pages an engine cites

domain_* — domain-level: am I cited, what for

Tool	Purpose
domain_am_i_cited	Domain citation check. With engine=auto (default): fans across all available LLM engines, returns per-engine breakdown + cross-engine consensus. Pin engine= to reduce cost.
domain_cited_for	Queries the domain has been cited for, from local cache
domain_cited_for_diff	Diff of domain_cited_for between two time windows for a domain

signals_* — external signals: AI Overview, Wikipedia, GSC, answer-box position

Tool	Purpose
signals_ai_overview	Google AI Overview presence + cited sources
signals_wikipedia	List Wikipedia articles referencing a domain (zero keys)
signals_gsc_gap	Join Google Search Console performance with AI citation status
signals_answer_box	Bin each citation's first mention in raw_answer into early/middle/late thirds

panel_* — saved query panels (editorial watchlists)

Tool	Purpose
panel_track	Save / load / list named query panels (editorial watchlists)
panel_run	Run a panel through domain_am_i_cited and snapshot to disk

report_* — turnkey reporting artifacts