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See how a website treats AI agents, and check whether a ChatGPT, Claude or Perplexity visit is real.

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Status
Healthy
Uptime
100.0% over the last 24 hours
Last Tested
Transport
Streamable HTTP · MCP 2025-11-25
URL
Repository
knocklog/api
GitHub Stars
0
ChatGPT
–
Claude
–

TDQS

A4.1/5.0

Scored across 3 tools

Disambiguation5/5

Each tool targets a clearly different object: classify_request analyzes a single live request, list_known_agents returns reference directory data, and scan_site audits an external website. Although classification draws on the same agent knowledge as the directory, the action and input shape are distinct enough that an agent would not misselect.

Naming Consistency5/5

All three names use a consistent snake_case verb_noun pattern (classify_request, list_known_agents, scan_site), with clear verbs indicating the operation. No mixed conventions or vague names.

Tool Count4/5

Three tools is on the thin side but each maps to a genuine, non-redundant workflow in a narrow domain. The set is focused rather than padded, though it sits at the lower boundary of what feels comfortably complete.

Completeness4/5

The core lifecycle — identify a request, look up known agents, and audit a site — is covered with no dead ends. Minor gaps exist: there is no batch classification, no retrieval of past classification results/logs, and no per-agent detail lookup beyond the directory listing.

Available Tools

3 tools
classify_requestIdentify and verify one HTTP requestA
Read-only
Inspect

Identifies whether a request comes from an AI agent, which one, what kind (training, AI search, user-triggered, agentic browser…) and whether its identity is verified or spoofed, using what each operator publishes (IP lists, reverse DNS, Web Bot Auth signatures; see https://knocklog.ai/agents). Pass the client IP, the full request URL and all request headers for the most complete check.

Inputs: ip, url, method, headers, +1 more.

list_known_agentsList known AI agentsA
Read-only
Inspect

Returns the directory of known AI agents and crawlers: operator, class, robots.txt token, whether they honour robots.txt, and how each can be verified. Optionally filter by agent_class.

Inputs: agent_class.

scan_siteScan a site for AI-agent readinessA
Read-only
Inspect

Checks a public website from the outside: which AI agents its robots.txt allows or blocks (training crawlers, AI search crawlers, user-triggered assistants), whether its content is readable without JavaScript, and whether it offers llms.txt and markdown. Returns a 0–100 score, a grade and prioritised findings with recommendations. Takes a few seconds.

Inputs: domain (required).

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

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