Citation Intelligence vs Firecrawl MCP Server | AllMCPs
Side-by-Side Model Context Protocol Comparison
Citation Intelligence vs Firecrawl MCP Server
In-depth architectural comparison of the Citation Intelligence and Firecrawl MCP Server MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.
At a Glance & Executive Verdict
Citation Intelligence
Search & Data Extraction · Local stdio
Quality: 57/100 (Good) | Auth: API Key required
Firecrawl MCP Server
Search & Data Extraction · Local stdio
Quality: 90/100 (Excellent) | Auth: API Key required
Verdict Summary: Choose Citation Intelligence if you need specialized Search & Data Extraction tools running via a local process. Choose Firecrawl MCP Server if your workspace requires Search & Data Extraction integration with local subprocess execution. Both servers can be configured concurrently in your client's mcpServers manifest.
Which MCP Server Should You Choose?
Choose Citation Intelligence when:
You need dedicated capabilities in the Search & Data Extraction domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: API Key required (BYOK (Pay Provider Direct)).
You have access to required keys: OPENAI_API_KEY, ANTHROPIC_API_KEY, GOOGLE_API_KEY, BING_API_KEY.
What LLMs cite, for agents. Check which URLs Perplexity, Claude, ChatGPT, Gemini, Bing, and Google AI Overviews cite for any query. Self-hosted, BYO API key. Install via npx @automatelab/citation-intelligence.
Official Firecrawl server to search the web and scrape, crawl, map, and extract structured data from any site for LLMs. Handles JS-rendered pages, PDFs, and batch jobs; hosted remote MCP with OAuth or self-host.
Tools & Capabilities Breakdown
Citation Intelligence Tools (26)
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 answers on. Requires at least one engine API key; auto-picks the first available.
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, product, or content site in AI search.
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.
domain_cited_for
List 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_predict
Ready-to-Paste Client Configurations
Paste either (or both) of these JSON server blocks into your client config file (e.g. claude_desktop_config.json or ~/.cursor/mcp.json).
Citation Intelligence is categorized under Search & Data Extraction and uses a local stdio subprocess. In contrast, Firecrawl MCP Server belongs to Search & Data Extraction using local stdio subprocess. Select Citation Intelligence when you need capabilities focused on search & data extraction and Firecrawl MCP Server when you require tools for search & data extraction.
Score 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_track
Save, 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_run
Run a saved panel through am_i_cited and append a timestamped snapshot. Side effects: makes external API calls to the configured AI engine (costs API quota); writes one snapshot file to disk at <config>/snapshots/<panel>/<iso>.json. Requires at least one engine API key (same as am_i_cited). Returns per-query citation presence and a citation_rate summary for the run. Use panel_track to create a panel first; use citations_trend to read the accumulated trend after multiple runs.
report_visibility
Turnkey AI visibility report for a domain across a query set. Composes check_citations over every query (or a saved panel) and returns the metrics AI-visibility trackers sell as a dashboard, in one call: mention frequency (citation_rate), share_of_voice vs competitors, average rank when cited, and brand sentiment from the answer text. Side effects: one check_citations call per query (costs API quota for uncached queries; cached queries are free). Returns structured summary + top_domains + per_query, plus a rendered Markdown report (include_markdown=true) suitable for a public page. Provide queries[] or a panel name. Same engine selection as check_citations.
citations_trend
Report citation rate over time for a panel from stored snapshots. Read-only; cache-only — makes no API calls to any AI engine and costs no API quota. Reads snapshot files from <config>/snapshots/<panel>/. Returns: snapshots[] (one entry per panel_run invocation, each with timestamp and citation_rate), plus per-query deltas (gained/lost/unchanged) comparing first vs last snapshot. Returns an empty series when no snapshots exist yet. No auth required. No rate limits. Use panel_run to accumulate snapshots first; use since to restrict the time window.
competitors_compare
Run 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_wikipedia
List Wikipedia articles that reference the given domain. Read-only. One HTTPS GET to the Wikipedia API (en.wikipedia.org/w/api.php?action=query&list=exturlusage). No auth required; no API keys; no rate limits beyond Wikipedia's public API fair-use policy (~1 request/second). Returns article titles and URLs. Wikipedia backlinks are the highest-lift signal for LLM training corpora — a domain cited from Wikipedia is far more likely to appear in AI training data and citation pools. Use lang to query non-English Wikipedias.
audit_sitemap
Fetch 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.
+14 more tools listed on main page
Firecrawl MCP Server Tools (25)
firecrawl_scrape
Retrieve and extract content from one supplied URL through Firecrawl. Use this when the request identifies a page and needs its content or defined fields. It can return markdown, HTML, links, screenshots, branding data, a targeted answer, or JSON matching a supplied schema; JSON is useful when the requested result has defined fields, while markdown preserves readable page content.
This tool operates on a known page. For a set of pages use `firecrawl_crawl`, and to discover page URLs use `firecrawl_map` or `firecrawl_search`. Options include JavaScript render delay, cache age, main-content filtering, PII redaction, and lockdown cache-only retrieval. Browser actions may change the live page when interactive actions are enabled.
Firecrawl may reuse recently indexed content instead of refetching the page, and the reuse window varies by domain. Set `maxAge: 0` to force a live fetch, or a smaller `maxAge` to bound how stale reused content may be. A successful response does not by itself confirm that the state it describes is still current.
Returns the selected content formats and page metadata.
firecrawl_map
Enumerate URLs indexed under one website through Firecrawl without fetching each page's content. Use this when the request asks for a site's URL inventory, when several relevant pages must be located, or when the desired page URL is unknown. An optional `search` term narrows the URL list, while sitemap, subdomain, query-parameter, and result-limit options control coverage.
Returns matching URLs rather than page bodies. Retrieve one page with `firecrawl_scrape`; collect content across multiple pages with `firecrawl_crawl`.
firecrawl_search
Search web, news, or image sources and return ranked results. Operators include quoted phrases, `-term`, `site:host`, `inurl:term`, `intitle:term`, and `related:host`; the set is non-exhaustive. `includeDomains` and `excludeDomains` are mutually exclusive hostname filters; categories limit results to GitHub, research, PDF, or developer sources.
For a programming question, add `categories: ["developer"]`. It searches an index of GitHub issues, merged pull requests, repository READMEs, and curated documentation sites, and returns the hits in `data.developer` beside the web results.
`categories: ["research"]` restricts these web results to research-affiliated websites and returns page snippets. The `firecrawl_research_*` tools are a separate surface that searches paper abstracts and full text across biomedical (PubMed, bioRxiv, medRxiv) and arXiv literature.
`scrapeOptions` can attach extracted page content; pages fetched this way use a fixed reuse window and ignore `maxAge`, so use `firecrawl_scrape` when a live fetch is required. Returns source-type result groups and usage metadata. Authenticated responses can include an `id` for optional search feedback.
firecrawl_crawl
Start a multi-page crawl at a website URL, poll it to a terminal state, and return the final status and collected data. Scope can be bounded with include/exclude paths, depth, page limit, subdomain/external-link controls, sitemap handling, delay, and scrape options.
Crawl results can be large; use conservative limits when full-site coverage is unnecessary. Webhooks and interactive scrape actions are unavailable in safe mode. Returns the crawl ID, status, and page data.
firecrawl_check_crawl_status
Retrieve the current status, progress, and available results for an existing crawl ID. This only reads Firecrawl job state and does not start or modify the crawl.
firecrawl_extract
Deprecated compatibility entry point. Use firecrawl_scrape once per known URL with formats: ["json"] and jsonOptions containing the prompt and schema. Use firecrawl_search or firecrawl_agent before Scrape when URLs are not known.
firecrawl_agent
Start an asynchronous web research job from a prompt, optional seed URLs, and an optional JSON schema. Use this for a requested synthesis across multiple sources when the task can wait for asynchronous completion. The agent can search, navigate, read pages, and assemble a structured result.
This call returns only a job ID, not the research result. Read the job with `firecrawl_agent_status` until it reaches `completed` or `failed`; research commonly takes several minutes. If the job cannot finish within the task's available time, `firecrawl_search` and `firecrawl_scrape` can gather evidence synchronously.
firecrawl_agent_status
Retrieve progress or final results for a `firecrawl_agent` job ID. A `processing` response is non-terminal and does not contain the final research result. Check again after 15–30 seconds until the status is `completed` or `failed`; complex jobs can take several minutes. If the job cannot finish within the task's available time, use `firecrawl_search` and `firecrawl_scrape` to complete the requested output.
Returns job status, progress information, and result data when completed.
firecrawl_interact
Open or reuse a live browser session to navigate a page, click controls, fill fields, or run browser code. Provide either `url` or `scrapeId`, and either a natural-language `prompt` or executable `code`; code can run as Bash, Python, or Node with a bounded timeout.
This acts on the live site, so actions such as form submission can create persistent external side effects. Returns execution output, stdout/stderr, exit status, and session viewing URLs.
firecrawl_interact_stop
Stop the live interact session associated with a `scrapeId` and release its resources. Returns a success confirmation.
firecrawl_parse
Parse one supported document into markdown, HTML, links, summary, targeted answers, or JSON matching a schema. Supported inputs include common HTML, PDF, Word, RTF, OpenDocument, and spreadsheet files; PDF parsing can be bounded with `pdfOptions.maxPages`.
Local MCP reads `filePath` from the server filesystem. Hosted MCP uses two calls: first provide `filePath` to receive upload instructions, upload locally, then call again with the returned `uploadRef`; do not send both fields together. Remote web URLs belong in `firecrawl_scrape`.
Set `redactPII` to request redaction of personally identifiable information in the returned content. `zeroDataRetention` requires an eligible authenticated account; omit it for anonymous keyless use. Returns upload instructions for hosted phase one or parsed document content for the final call.
firecrawl_monitor_create
Create a recurring scrape, crawl, or search monitor that compares each check with its retained predecessor. The simple form accepts `page`/`pages` or `queries` plus a plain-language `goal`; the advanced `body` form controls targets, schedule, change-tracking formats, judging, retention, webhook, and notifications.
In the simple form, a `goal` is required. If `queries` contains one or more non-empty values and is supplied with `page`/`pages`, `queries` create the search target and page targets are ignored. A monitor schedules future network checks and can send configured email or webhook notifications. Returns the created monitor.