{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"npm_npm-firecrawl-mcp","slug":"npm-firecrawl-mcp","name":"firecrawl-mcp","type":"mcp","url":"https://www.npmjs.com/package/firecrawl-mcp","page_url":"https://unfragile.ai/npm-firecrawl-mcp","categories":["mcp-servers"],"tags":["mcp","firecrawl","web-search","web-data","web-interaction"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"npm_npm-firecrawl-mcp__cap_0","uri":"capability://tool.use.integration.mcp.native.web.scraping.with.cloud.and.self.hosted.routing","name":"mcp-native web scraping with cloud and self-hosted routing","description":"Exposes Firecrawl's web scraping engine through the Model Context Protocol (MCP), enabling LLM agents to invoke scraping operations as native tools. Routes requests to either Firecrawl's cloud infrastructure or self-hosted instances based on configuration, abstracting transport complexity behind a unified MCP resource interface. Implements request/response marshaling to convert between MCP's JSON-RPC protocol and Firecrawl's REST API contract.","intents":["I want my Claude/LLM agent to scrape web pages as a native tool without managing HTTP clients","I need to switch between cloud and self-hosted Firecrawl without changing agent code","I want to expose web scraping capabilities to multiple LLM clients via a single MCP server"],"best_for":["AI agent developers building multi-tool systems with Claude or other MCP-compatible LLMs","Teams running self-hosted Firecrawl instances who want LLM integration without custom API wrappers","Enterprises requiring on-premise data processing with LLM-driven web intelligence"],"limitations":["MCP protocol overhead adds ~50-100ms per request compared to direct REST calls due to JSON-RPC serialization","Requires MCP client support — not all LLM platforms natively support MCP servers yet","No built-in request queuing or rate-limiting — relies on underlying Firecrawl instance limits","Self-hosted routing requires manual configuration; no automatic failover between cloud and self-hosted"],"requires":["Node.js 16+ (for MCP server runtime)","Firecrawl API key (for cloud) OR self-hosted Firecrawl instance URL","MCP-compatible LLM client (Claude with MCP support, or custom MCP client)","Network access to Firecrawl cloud or self-hosted endpoint"],"input_types":["URL string","JSON configuration object (headers, cookies, timeout, proxy settings)"],"output_types":["Scraped HTML/markdown content","Structured JSON metadata (title, description, links)","LLM-ready formatted text"],"categories":["tool-use-integration","mcp-server"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-firecrawl-mcp__cap_1","uri":"capability://data.processing.analysis.url.to.structured.data.extraction.with.llm.powered.schema.mapping","name":"url-to-structured-data extraction with llm-powered schema mapping","description":"Accepts a URL and optional JSON schema, then uses Firecrawl's backend to fetch the page and extract structured data matching the provided schema. The extraction leverages LLM inference (via Firecrawl's backend) to intelligently map page content to schema fields, handling variations in HTML structure and content layout. Returns validated JSON conforming to the schema, enabling downstream processing without manual parsing.","intents":["I want to extract product details (price, rating, availability) from e-commerce pages into a consistent JSON format","I need to scrape job listings and normalize them into a standard job posting schema","I want to extract structured data from unstructured web content without writing CSS selectors or regex"],"best_for":["Data engineers building web-to-database pipelines with schema-driven extraction","AI agents that need to normalize heterogeneous web content into structured formats","Non-technical users who want to extract data without learning CSS selectors or XPath"],"limitations":["Schema inference accuracy depends on page content clarity — ambiguous or sparse data may result in null fields","LLM-based extraction adds latency (typically 2-5 seconds per page) compared to regex/CSS selector approaches","Large schemas (50+ fields) may exceed token limits or require multiple inference passes","No built-in schema validation — malformed schemas are passed to backend without client-side checking"],"requires":["Valid URL pointing to publicly accessible web page","Optional JSON schema (if omitted, returns raw extracted content)","Firecrawl API key with extraction capability enabled","Page must be renderable (JavaScript-heavy sites may require headless browser option)"],"input_types":["URL string","JSON schema object (OpenAPI/JSON Schema format)","Optional extraction options (wait for selector, timeout, proxy)"],"output_types":["JSON object conforming to provided schema","Extraction metadata (confidence scores, field coverage)","Raw extracted content if no schema provided"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-firecrawl-mcp__cap_10","uri":"capability://automation.workflow.rate.limiting.and.quota.management.with.per.request.tracking","name":"rate limiting and quota management with per-request tracking","description":"Tracks API quota usage per request and enforces client-side rate limits to prevent exceeding Firecrawl's quota. Maintains running counters of requests, bytes processed, and API costs. Provides quota status queries and warnings when approaching limits. Implements token bucket or sliding window rate limiting to smooth request distribution.","intents":["I want to monitor my Firecrawl API quota usage in real-time","I need to enforce rate limits to avoid exceeding my plan's monthly quota","I want to get warnings when approaching quota limits so I can adjust my scraping"],"best_for":["Cost-conscious teams managing Firecrawl quota across multiple agents","Long-running scraping pipelines that need quota visibility","Multi-tenant systems allocating quota across users"],"limitations":["Client-side rate limiting is approximate; actual Firecrawl backend limits may differ","No built-in quota sharing across multiple MCP server instances — each server tracks independently","Quota reset timing (daily/monthly) must be manually configured; no automatic sync with Firecrawl backend","Rate limiting adds minimal overhead (~1-5ms per request) but requires memory for tracking"],"requires":["Firecrawl API key with quota information","Optional: rate limit configuration (requests per second, bytes per hour, monthly quota)","Optional: persistent quota store (Redis, database) for cross-instance tracking"],"input_types":["Rate limit configuration (requestsPerSecond, bytesPerHour, monthlyQuota)","Query for quota status"],"output_types":["Quota status object (used, remaining, resetTime)","Rate limit metadata (current rate, queue depth)","Warnings when approaching limits"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-firecrawl-mcp__cap_11","uri":"capability://automation.workflow.streaming.and.incremental.content.delivery.for.large.pages","name":"streaming and incremental content delivery for large pages","description":"Supports streaming scraped content incrementally as it becomes available, rather than buffering entire pages in memory. Useful for large pages (10MB+) that would exceed memory limits or cause long latencies if fully buffered. Returns content as a stream of chunks with optional progress callbacks. Enables real-time content processing without waiting for full page completion.","intents":["I want to process large web pages without loading the entire content into memory","I need to start processing content as soon as the first chunks arrive, not wait for full page","I want to display scraping progress to users in real-time"],"best_for":["Large-scale scraping pipelines processing multi-megabyte pages","Real-time content processing systems that need low latency","Memory-constrained environments (edge computing, serverless functions)"],"limitations":["Streaming adds complexity to error handling — errors mid-stream may result in partial content","Content-based deduplication and caching are incompatible with streaming (requires full content hash)","Structured data extraction may be impossible on partial content — requires buffering for schema validation","Progress callbacks add overhead; frequent callbacks may impact performance"],"requires":["URL pointing to large content","Firecrawl API key with streaming support","Optional: progress callback function"],"input_types":["URL string","Streaming options (chunkSize, progressCallback)"],"output_types":["Readable stream of content chunks","Progress metadata (bytesReceived, estimatedTotal, percentComplete)","Error events for mid-stream failures"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-firecrawl-mcp__cap_12","uri":"capability://data.processing.analysis.custom.extraction.rules.and.css.selector.fallback","name":"custom extraction rules and css selector fallback","description":"Allows users to define custom extraction rules using CSS selectors, XPath, or regex patterns as fallback when LLM-based schema extraction fails or is unavailable. Supports rule composition (multiple selectors with AND/OR logic) and field mapping. Provides deterministic, fast extraction for well-structured pages without LLM latency.","intents":["I want to extract data using CSS selectors for pages with consistent HTML structure","I need a fast, deterministic extraction method that doesn't rely on LLM inference","I want to define custom extraction rules for specific websites"],"best_for":["Developers comfortable with CSS selectors and XPath","High-performance scraping pipelines where LLM latency is unacceptable","Extraction from pages with consistent, predictable HTML structure"],"limitations":["CSS selectors are brittle — page layout changes break extraction rules","XPath is complex and error-prone; requires deep HTML knowledge","No automatic rule generation — rules must be manually written and tested","Regex patterns are limited to text extraction; cannot handle nested structures","Rule composition (AND/OR) adds complexity; no visual rule builder"],"requires":["CSS selectors, XPath, or regex patterns for target elements","Knowledge of target page's HTML structure","Firecrawl API key"],"input_types":["URL string","Extraction rules object (selectors, xpath, regex patterns, field mapping)"],"output_types":["Extracted data matching rule definitions","Extraction metadata (matched elements count, rule coverage)"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-firecrawl-mcp__cap_2","uri":"capability://automation.workflow.batch.web.scraping.with.job.queuing.and.result.aggregation","name":"batch web scraping with job queuing and result aggregation","description":"Accepts an array of URLs and optional scraping parameters, then submits them to Firecrawl's batch processing pipeline. Implements asynchronous job tracking with polling or webhook callbacks, aggregating results as jobs complete. Handles partial failures gracefully, returning per-URL status (success/error) alongside extracted content. Enables efficient processing of 10s-1000s of pages without blocking the MCP client.","intents":["I want to scrape 500 product pages and get results back without waiting for sequential requests","I need to monitor batch scraping progress and handle failures per-URL without reprocessing successful pages","I want to extract data from a list of URLs and aggregate results into a single dataset"],"best_for":["Data pipeline engineers processing large URL lists (100+ URLs)","Researchers collecting web data at scale with fault tolerance","AI agents that need to gather information from multiple sources in parallel"],"limitations":["Batch processing introduces latency — results are not immediately available; polling adds 1-5 second overhead per status check","Firecrawl cloud has rate limits and concurrent job caps; batch size is constrained by backend capacity","No built-in deduplication — duplicate URLs in batch are processed separately, wasting quota","Webhook callbacks require publicly accessible endpoint; polling is simpler but less efficient for large batches","Failed jobs are not automatically retried — requires manual resubmission logic"],"requires":["Array of valid URLs (minimum 2, typically up to 1000 per batch)","Firecrawl API key with batch processing tier enabled","For webhook callbacks: publicly accessible HTTP endpoint with HTTPS","Sufficient Firecrawl quota for batch size (cloud plans have monthly/concurrent limits)"],"input_types":["Array of URL strings","Batch options object (timeout, retry policy, webhook URL, extraction schema)"],"output_types":["Batch job ID (for tracking)","Array of per-URL results with status (success/failed), content, and metadata","Aggregated statistics (success rate, total processing time)"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-firecrawl-mcp__cap_3","uri":"capability://search.retrieval.web.search.with.firecrawl.integration.for.result.scraping","name":"web search with firecrawl integration for result scraping","description":"Accepts a search query and optional parameters (number of results, search engine, language), then uses Firecrawl's search capability to find URLs and optionally scrape the top results. Combines search index lookup with on-demand scraping, returning both search metadata (title, snippet, URL) and full page content. Enables LLM agents to research topics by searching and immediately extracting relevant information.","intents":["I want my agent to search for information and automatically scrape the top results without manual URL collection","I need to find and extract structured data from search results (e.g., product prices across multiple sites)","I want to augment LLM knowledge with current web information by searching and scraping in one operation"],"best_for":["AI agents that need real-time web research capabilities","Competitive intelligence tools that search and extract data from competitor websites","LLM applications requiring current information beyond training data cutoff"],"limitations":["Search results are limited to Firecrawl's search index; coverage may be incomplete for niche topics or recent content","Scraping all results multiplies latency — typically 5-15 seconds for 5-10 results due to per-page processing","Search engine rate limits apply; excessive searches may trigger temporary blocks","No built-in result ranking or relevance filtering — returns raw search results in order","Requires internet connectivity; cannot work offline or with private/internal content"],"requires":["Search query string (1-100 characters)","Firecrawl API key with search capability enabled","Optional: search engine preference (Google, Bing, etc.) if supported by Firecrawl","Network access to search index and target websites"],"input_types":["Search query string","Search options (number of results, language, region, search engine)","Optional scraping schema for extracted results"],"output_types":["Array of search results with metadata (title, snippet, URL, rank)","Optionally: full scraped content for top results","Search metadata (total results found, search time)"],"categories":["search-retrieval","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-firecrawl-mcp__cap_4","uri":"capability://data.processing.analysis.markdown.formatted.content.extraction.for.llm.consumption","name":"markdown-formatted content extraction for llm consumption","description":"Scrapes a URL and returns content formatted as clean, LLM-optimized markdown with preserved structure (headings, lists, tables, code blocks). Removes boilerplate (navigation, ads, footers) and normalizes formatting to maximize token efficiency and readability for language models. Includes optional metadata extraction (title, author, publish date) in YAML frontmatter.","intents":["I want to feed web content to my LLM agent in a clean, structured format without HTML noise","I need to extract article text with metadata (title, date) for content analysis or summarization","I want to preserve document structure (headings, lists) when scraping for better LLM understanding"],"best_for":["LLM application developers who need clean content for prompting","Content analysis pipelines that require structured markdown input","Researchers extracting text from web articles for NLP processing"],"limitations":["Markdown conversion is lossy — complex CSS layouts, custom styling, and interactive elements are not preserved","Boilerplate removal heuristics may incorrectly strip relevant content on non-standard page layouts","Tables are converted to markdown format which may be less precise than HTML for complex structures","Metadata extraction (author, date) relies on heuristics and may fail on pages without standard meta tags"],"requires":["Valid URL pointing to text-heavy content (articles, documentation, blog posts)","Firecrawl API key with markdown formatting enabled","Page should be publicly accessible and not require authentication"],"input_types":["URL string","Optional formatting options (include metadata, preserve code blocks, table format)"],"output_types":["Markdown-formatted string with optional YAML frontmatter","Extracted metadata (title, author, publish date, word count)","Content structure metadata (headings, sections)"],"categories":["data-processing-analysis","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-firecrawl-mcp__cap_5","uri":"capability://data.processing.analysis.javascript.rendered.content.scraping.with.headless.browser.support","name":"javascript-rendered content scraping with headless browser support","description":"Scrapes URLs that require JavaScript execution by delegating to Firecrawl's headless browser backend (Puppeteer/Playwright). Waits for specified selectors or timeouts to ensure dynamic content is fully loaded before extraction. Supports cookie/session injection for authenticated scraping. Returns fully rendered HTML or extracted content after JavaScript execution completes.","intents":["I want to scrape single-page applications (React, Vue, Angular) that load content via JavaScript","I need to extract data from pages that require login or session cookies","I want to wait for dynamic content (infinite scroll, lazy loading) to load before scraping"],"best_for":["Web scraping engineers handling modern JavaScript-heavy websites","Data collectors working with SPA frameworks and dynamic content","Researchers needing authenticated access to web content"],"limitations":["Headless browser rendering adds significant latency (5-15 seconds per page) compared to static HTML scraping","Firecrawl cloud has limited concurrent browser instances; batch rendering may queue or timeout","Session/cookie injection requires manual credential management; no built-in secret management","Some anti-bot detection (Cloudflare, reCAPTCHA) may block headless browser requests","Memory usage is high; large-scale rendering of many pages simultaneously may exhaust resources"],"requires":["Valid URL pointing to JavaScript-rendered content","Firecrawl API key with browser rendering capability enabled","Optional: cookies/session tokens for authenticated scraping","Optional: CSS selector for wait condition (e.g., '.content-loaded')"],"input_types":["URL string","Browser options (wait selector, timeout, cookies, user agent, viewport size)","Optional extraction schema for structured data"],"output_types":["Fully rendered HTML after JavaScript execution","Extracted content (markdown or structured data)","Rendering metadata (execution time, final URL after redirects)"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-firecrawl-mcp__cap_6","uri":"capability://data.processing.analysis.intelligent.content.filtering.and.boilerplate.removal","name":"intelligent content filtering and boilerplate removal","description":"Automatically detects and removes non-content elements (navigation menus, sidebars, ads, footers, cookie banners) from scraped pages using heuristic analysis and optional ML-based content detection. Preserves main article/content body while stripping structural noise. Configurable aggressiveness levels allow tuning between content preservation and noise removal.","intents":["I want to extract just the article text without navigation, ads, or sidebar content","I need to clean scraped content for downstream NLP processing without manual filtering","I want to maximize signal-to-noise ratio when feeding content to LLMs"],"best_for":["Content extraction pipelines processing diverse website layouts","LLM applications that need clean, focused content for analysis","Data scientists preparing web-scraped text for NLP models"],"limitations":["Heuristic-based filtering may incorrectly remove relevant content on non-standard layouts (e.g., multi-column articles, sidebar content that's part of main narrative)","No configuration per-site — filtering rules are global and may not suit all content types","Aggressive filtering may strip important metadata or related content links","Performance impact is minimal but adds ~100-200ms per page"],"requires":["Scraped HTML or markdown content","Firecrawl API key (filtering is applied server-side)","Optional: aggressiveness level configuration"],"input_types":["URL string or raw HTML","Filtering options (aggressiveness level, preserve links, preserve metadata)"],"output_types":["Cleaned HTML or markdown with boilerplate removed","Content quality metadata (estimated content percentage, removed elements count)"],"categories":["data-processing-analysis","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-firecrawl-mcp__cap_7","uri":"capability://automation.workflow.caching.and.deduplication.for.repeated.url.scraping","name":"caching and deduplication for repeated url scraping","description":"Maintains a cache of previously scraped URLs within a configurable TTL (time-to-live), returning cached results for duplicate requests without re-scraping. Implements content-based deduplication to detect semantically identical pages (same content, different URLs). Reduces API quota usage and latency for repeated scraping patterns.","intents":["I want to avoid re-scraping the same URL multiple times in a single agent session","I need to detect when multiple URLs point to the same content and avoid duplicate processing","I want to reduce Firecrawl API quota usage by caching results"],"best_for":["Long-running agents that may encounter repeated URLs","Batch processing pipelines with potential URL duplicates","Cost-conscious teams optimizing API quota usage"],"limitations":["Cache is in-memory by default; not persisted across MCP server restarts","TTL is global; no per-URL cache expiration configuration","Content-based deduplication requires computing content hashes, adding ~50ms per page","Cache size is unbounded; large-scale scraping may exhaust memory","No cache invalidation mechanism — stale content may be returned if page updates frequently"],"requires":["MCP server running with cache enabled (default)","Optional: cache TTL configuration (default 1 hour)","Optional: persistent cache backend (Redis, file-based) for cross-session caching"],"input_types":["URL string","Cache options (TTL, enable deduplication, cache key strategy)"],"output_types":["Cached or freshly scraped content","Cache hit/miss metadata","Deduplication results (if duplicate detected)"],"categories":["automation-workflow","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-firecrawl-mcp__cap_8","uri":"capability://tool.use.integration.proxy.and.header.injection.for.geolocation.and.authentication","name":"proxy and header injection for geolocation and authentication","description":"Supports custom HTTP headers, proxy URLs, and user-agent strings to enable scraping from different geographic regions, bypassing IP-based restrictions, and authenticating to protected resources. Passes proxy and header configuration to Firecrawl's backend, which applies them during page fetch. Enables scraping of geo-restricted or authentication-required content.","intents":["I want to scrape content from different geographic regions (e.g., localized pricing pages)","I need to bypass IP-based rate limiting or geo-blocking by using a proxy","I want to scrape authenticated content by injecting session cookies or authorization headers"],"best_for":["Web scraping engineers handling geo-restricted or authenticated content","Competitive intelligence tools monitoring regional pricing or availability","Researchers collecting data from multiple geographic markets"],"limitations":["Proxy usage adds latency (typically 1-3 seconds per request) depending on proxy quality","Proxy credentials are transmitted in plaintext to Firecrawl backend; requires trust in infrastructure","Some websites detect and block proxy traffic; no built-in proxy rotation or fallback","Custom headers may be overwritten by Firecrawl's own headers (e.g., User-Agent)","No built-in credential management; secrets must be injected at runtime"],"requires":["Valid proxy URL (http://proxy-host:port or socks5://proxy-host:port)","Optional: proxy authentication credentials","Optional: custom headers (Authorization, Cookie, User-Agent, etc.)","Firecrawl API key"],"input_types":["URL string","Proxy configuration (URL, credentials, protocol)","Custom headers object (key-value pairs)","User-agent string"],"output_types":["Scraped content as if requested from proxy location","Response headers (may include geolocation indicators)","Proxy metadata (latency, success/failure)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-firecrawl-mcp__cap_9","uri":"capability://automation.workflow.error.handling.and.retry.logic.with.exponential.backoff","name":"error handling and retry logic with exponential backoff","description":"Implements automatic retry logic for transient failures (timeouts, rate limits, temporary server errors) using exponential backoff with configurable max retries and backoff multiplier. Distinguishes between retryable errors (429, 503) and permanent failures (404, 403), avoiding wasted retries on unrecoverable errors. Returns detailed error information including failure reason, retry count, and final status.","intents":["I want my scraping to automatically retry on temporary failures without manual intervention","I need to handle rate limiting gracefully by backing off and retrying","I want detailed error information to debug scraping failures"],"best_for":["Robust scraping pipelines that need fault tolerance","Long-running agents that encounter transient network issues","Large-scale batch processing where some failures are expected"],"limitations":["Exponential backoff increases total latency for failing requests (e.g., 3 retries = 1+2+4 = 7 seconds base delay)","Retry logic is applied per-request; no global rate limit coordination across concurrent requests","Max retries is fixed per request; no adaptive retry strategy based on error patterns","Permanent errors (4xx) are not retried, which is correct but may mask transient 4xx errors"],"requires":["Firecrawl API key","Optional: retry configuration (max retries, backoff multiplier, initial delay)"],"input_types":["URL string","Retry options (maxRetries, backoffMultiplier, initialDelayMs)"],"output_types":["Scraped content on success","Detailed error object with retryCount, finalError, and retryable flag","Retry metadata (total time spent retrying, final status code)"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":32,"verified":false,"data_access_risk":"high","permissions":["Node.js 16+ (for MCP server runtime)","Firecrawl API key (for cloud) OR self-hosted Firecrawl instance URL","MCP-compatible LLM client (Claude with MCP support, or custom MCP client)","Network access to Firecrawl cloud or self-hosted endpoint","Valid URL pointing to publicly accessible web page","Optional JSON schema (if omitted, returns raw extracted content)","Firecrawl API key with extraction capability enabled","Page must be renderable (JavaScript-heavy sites may require headless browser option)","Firecrawl API key with quota information","Optional: rate limit configuration (requests per second, bytes per hour, monthly quota)"],"failure_modes":["MCP protocol overhead adds ~50-100ms per request compared to direct REST calls due to JSON-RPC serialization","Requires MCP client support — not all LLM platforms natively support MCP servers yet","No built-in request queuing or rate-limiting — relies on underlying Firecrawl instance limits","Self-hosted routing requires manual configuration; no automatic failover between cloud and self-hosted","Schema inference accuracy depends on page content clarity — ambiguous or sparse data may result in null fields","LLM-based extraction adds latency (typically 2-5 seconds per page) compared to regex/CSS selector approaches","Large schemas (50+ fields) may exceed token limits or require multiple inference passes","No built-in schema validation — malformed schemas are passed to backend without client-side checking","Client-side rate limiting is approximate; actual Firecrawl backend limits may differ","No built-in quota sharing across multiple MCP server instances — each server tracks independently","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.5,"ecosystem":0.45,"match_graph":0.25,"freshness":0.52,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:23.903Z","last_scraped_at":"2026-05-03T14:23:53.530Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=npm-firecrawl-mcp","compare_url":"https://unfragile.ai/compare?artifact=npm-firecrawl-mcp"}},"signature":"KAt43Mt4yb5VZ8WzArccofaEJ/3r1ytmzncP87VoddVZWZD+SL9H065lF2kDsRfFmmIVNUwHGrNZLbPNvpklCg==","signedAt":"2026-06-20T05:32:44.978Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/npm-firecrawl-mcp","artifact":"https://unfragile.ai/npm-firecrawl-mcp","verify":"https://unfragile.ai/api/v1/verify?slug=npm-firecrawl-mcp","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}