Anakin

@anakin list all active monitors and show me which ones detected changes in the last 24 hours

Found 4 active monitors in your account. Two have detected changes: 'Competitor Pricing Page' (last changed 6 hours ago, extracted price increased from $49 to $59) and 'Regulatory Compliance Doc' (changed 18 hours ago, new section added). 'Product Changelog' and 'API Status Page' show no changes since their last checks. All monitors are consuming credits on their scheduled intervals—Competitor Pricing runs every 2 hours, Compliance Doc runs daily.

This example shows the MCP's read-only monitoring capabilities. Each active monitor consumes credits on its schedule whether or not changes are detected. You'll need to manage monitor lifecycles explicitly—pausing or deleting unused monitors—to control credit burn. The MCP returns structured extraction results when configured, making it useful for tracking specific data points across recurring checks.

@anakin create a monitor for https://example.com/releases that checks every 6 hours and extracts version numbers and release dates

Monitor created successfully (ID: mon_8k3j2). Configured to check https://example.com/releases every 6 hours with browser rendering enabled and structured extraction for version numbers and release dates. First check will run immediately, then repeat on schedule. You'll receive change alerts when new content is detected. This monitor will consume approximately 120 credits per day (4 checks × 30 credits per rendered page). Current account balance: 8,450 credits.

This demonstrates the MCP's write capability for setting up recurring surveillance. Browser rendering and structured extraction increase per-check credit costs significantly compared to simple HTML fetches. The monitor runs indefinitely until you pause or delete it—there's no automatic expiration. If the target site blocks automated access or changes structure, extraction may fail silently until you review snapshots manually.

@anakin run an agentic search on 'latest security vulnerabilities in React 18' and summarize the findings with source citations

Agentic search completed in 47 seconds. Found 12 relevant sources across security advisories, GitHub issues, and technical blogs. Key findings: Three moderate-severity XSS vulnerabilities patched in React 18.2.0 (CVE-2023-XXXX series), one critical SSR hydration issue fixed in 18.3.0, and ongoing discussion about Suspense boundary error handling. The synthesis identifies that teams on React 18.0–18.1 should prioritize upgrading to 18.3.0. Sources include official React blog, Snyk vulnerability database, and two independent security researchers. Total credit cost: 850 credits.

This showcases the MCP's AI-powered research synthesis, which goes beyond simple search to analyze and structure findings. Agentic searches are expensive (typically 500–1000 credits) and asynchronous—you must poll for completion. The quality of synthesis depends on query specificity and available sources. This is best for one-off research tasks, not recurring monitoring, because credit costs accumulate quickly with repeated use.

When scheduled crawls beat manual checks for pricing intel

A 6-person growth team at a B2B SaaS company needs to track three competitors' pricing pages weekly without burning analyst hours. Anakin's Create Monitor tool schedules browser-rendered crawls that capture structured data (plan names, price points, feature flags) and fire Slack alerts on changes. The team sets up three monitors, each checking Sunday night, and reviews diffs in Monday standup. This works cleanly if competitors update pricing monthly or quarterly—frequent enough to matter, rare enough that alert fatigue stays low. If your competitors ship daily micro-changes or you need sub-hour latency, monitors will flood your queue and you're better off with a real-time scraping service. For the weekly cadence case, Anakin's 26-tool surface gives you one place to schedule, extract, and alert without duct-taping Zapier to a headless browser.

Checking where your brand shows up in LLM answers

A 3-person marketing team at a developer-tools startup wants to know if ChatGPT, Perplexity, and Claude mention their product when users ask "best CI/CD tools for small teams." They use Get AI Visibility Search to run the same query across engines, then compare verdicts, latency, and whether their docs surfaced in citations. This is a monthly audit, not a daily dashboard—Anakin returns structured answers and credit costs per engine, so the team can spot which models ignore them and prioritize SEO or partnership plays accordingly. If you need real-time monitoring or want to test hundreds of queries, the per-search credit burn adds up fast and you'll want a dedicated AI search API. For quarterly or monthly brand-visibility checks across 3-5 engines, Anakin's multi-engine sweep is faster than running manual searches in five browser tabs.

When Wire actions replace Zapier for one-off site tasks

A 4-person support team at a niche SaaS handles 20 tickets a week that require logging into a partner portal, updating a field, and screenshotting proof for the customer. They build a Wire action in Anakin that authenticates once, accepts a ticket ID as a parameter, navigates the partner UI, submits the update, and returns a confirmation screenshot. Execute Wire Action kicks off the job asynchronously; the support agent pastes the job ID into the ticket and checks back in 90 seconds. This beats Zapier when the partner site has no API and you need browser-level interaction with session state. If your team runs 100+ of these a day, the per-job credit cost and 90-second latency become friction—you'd want a dedicated RPA tool or to lobby the partner for an API. For low-volume, high-touch workflows where you'd otherwise pay an intern to click through a UI, Anakin's parameterized actions are the pragmatic middle ground.