Lyrenth MCP vs Agentfetch MCP

read_url

The page as a clean AIDocument: a short provenance header (token count + how much smaller than raw HTML) plus the Markdown body. `fresh: true` forces a fresh fetch instead of the cached copy; `max_tokens` caps the body to your context budget, trimmed at a clean paragraph or sentence boundary.

read_urls

Up to 20 pages in one call, each as a clean AIDocument, with per-URL error isolation (a failed URL is reported and doesn't block the others). Billed one credit per successfully-read URL.

check_usage

Your plan tier, credits used against your monthly limit, credits remaining, and the reset date.

fetch_url

Fetch any URL and return clean, LLM-ready Markdown with token count, metadata, and 6h caching. WHEN TO USE: - You have a specific URL whose content you need. - You want to cap response size to stay inside your context window. - You want repeat fetches to be cheap (cache hits ≈ $0.0001). - The URL might be JS-rendered, a PDF, or behind a paywall — this tool auto-routes to the right fetcher (Trafilatura → Jina → FireCrawl → PDF). WHEN NOT TO USE: - You don't know which URL to fetch — use search_and_fetch instead. - You have many URLs to fetch — use fetch_multiple instead. Args: url: The URL to fetch. max_tokens: Hard cap on response size. Default unlimited. Pass this if you're tight on context budget — cheaper than over-fetching. format: "markdown" (default — recommended), "text", or "json". use_cache: True returns a cached copy if one exists (≤6h old). Pass False only when freshness matters (live news, prices). Returns: { "url": str, "success": bool, "markdown": str, "metadata": {title, author, published_date, domain, word_count, token_count, reading_time_seconds, content_type, language}, "cache": {hit, cached_at, expires_at}, "fetch_info": {fetcher_used, fetch_time_ms, cost_credits}, "error": str | None }