Agentfetch MCP vs Web Search

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 }

estimate_tokens

Estimate token count of a URL's content WITHOUT fetching the body. WHEN TO USE: - You're considering fetching a URL but unsure if it fits your remaining context window. This call is ~10x cheaper than a full fetch. - You want to triage a list of candidate URLs before deciding which to actually retrieve. IMPORTANT: Many servers omit Content-Length on dynamic / chunked responses. When that happens, this tool returns confident=false and estimated_tokens=null. In that case, call fetch_url with a max_tokens cap instead of trusting the estimate. Args: url: The URL to estimate. Returns: { "url": str, "success": bool, "estimated_tokens": int | null, "byte_size": int | null, "content_type": str, "confident": bool, "note": str }