Agent Monitor

Key Features

• •AI Bot Classification: Automatically identifies and labels traffic from AI crawlers such as ChatGPT-User, Gemini, and Claude-Web. Organizes bots by operator—OpenAI, Google, Anthropic—and ranks the most active ones for immediate insight.
• •URL Inspector: Checks any page on your domain to reveal if AI bots have visited, how recently and how frequently, and how many human users arrived after an AI assistant linked to it. Turns AI visibility into a measurable metric you can improve week over week.
• •AI Citations: Shows exactly how ChatGPT and similar models interact with your content, including fetch frequency, pages they deem authoritative enough to recommend, and autonomous visits from retrieval agents. Reveals your most cited pages as a blueprint for content replication.
• •Human vs AI Traffic Split: Compares genuine human visitors with AI and non-AI bot hits in a single dashboard view. Surfaces the buried 60% of traffic that GA4 filters out, enabling accurate attribution and resource allocation.
• •Server-Side Data Collection: Gathers traffic events directly from your server via WordPress, PrestaShop, Cloudflare Worker, or NPM package. This cookie-less approach bypasses ad blockers and client-side restrictions, ensuring every valid request is counted without added latency or legal consent friction.
• •Detailed Bot Profiles: For each detected bot, provides operator identity, historical activity charts, user-agent strings, and a list of pages visited. Empowers nuanced analysis of how different AI systems consume your site’s content.
• •Global AI Page Ranking: Aggregates data across all monitored bots to show which pages are most frequently visited by AI crawlers in aggregate. Helps prioritize optimization efforts toward pages with the highest AI engagement potential.

Use Cases

• •An SEO agency monitors client websites to prove that AI models are ignoring their content. Using Agent Monitor’s URL Inspector, the agency identifies pages with zero crawler visits and adjusts technical SEO elements, then validates improvement when AI agents begin fetching those pages within a week.
• •A content marketing manager wants to know if their in-depth guides influence AI recommendations. AI Citations reveals which articles ChatGPT cites most often. The manager analyzes common traits among top pages and replicates them across the blog, leading to a measurable increase in organic referrals from AI assistants.
• •An e-commerce store owner suspects their product pages are invisible to AI shopping agents. Agent Monitor shows that GoogleOther and ChatGPT shopping bots are not crawling new inventory. After a server-side integration audit, they correct blocking directives and start receiving AI-attributed traffic in the dashboard’s human-from-AI count.
• •A Node.js SaaS company integrates Agent Monitor via the NPM package to track AI crawler activity on their app documentation. They discover that ClaudeBot heavily fetches a particular integration guide but other guides are ignored. They improve internal linking and soon see a more balanced crawl pattern, expanding their visibility across AI ecosystems.
• •A digital agency pitches a new SEO service by sharing an Agent Monitor dashboard screenshot with a prospect. The prospect sees that 25% of their traffic comes from AI bots but generates zero measurable conversions. The agency then uses the tool to align the prospect’s content with AI recommendation patterns, creating a new revenue stream.
• •A growth lead at a B2B platform uses the free plan to monitor a single site. After confirming that AI bots actively visit their pricing and case study pages, they upgrade to a paid plan to track five more properties and set up a monthly reporting cadence for the leadership team, shifting AI visibility from a guess to a KPI.

Who is this for?

SEO specialists and agencies who need to audit and improve AI search visibility for clients. Digital marketing managers and content strategists responsible for organic traffic growth in an AI-driven search landscape. E-commerce operators and website owners who rely on accurate traffic attribution to gauge performance. Technical founders and product leads at SaaS companies that want their documentation and landing pages surfaced in AI-generated answers. Additionally, Node.js developers and DevOps engineers tasked with implementing server-side tracking solutions on modern web stacks.