About Knocklog
Knocklog is an analytics API for site owners tracking AI-agent visits, request identity, and referrals from AI assistants. Its endpoints cover agent verification, traffic reports, and project management.
Key features
- 01Identify and verify AI-agent requests
- 02Scan how a site treats agents
- 03Report AI-agent traffic
- 04Import access logs
- 05Configure webhooks and integrations
Use cases
- 01Check whether a crawler request is genuine
- 02Review pages read by AI agents
- 03Measure visitors and leads sent by AI assistants
MCP support
Knocklog offers MCP access through public directory, account-specific, and full-tool endpoints. MCP clients can use its agent and analytics capabilities.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://api.knocklog.ai/mcp/directoryclaude mcp add --transport http leonlesenechal-knocklog https://api.knocklog.ai/mcp/directory{"mcpServers":{"leonlesenechal-knocklog":{"type":"http","url":"https://api.knocklog.ai/mcp/directory"}}}Open in Cursor{"servers":{"leonlesenechal-knocklog":{"type":"http","url":"https://api.knocklog.ai/mcp/directory"}}}Open in VS Code{"mcpServers":{"leonlesenechal-knocklog":{"type":"http","url":"https://api.knocklog.ai/mcp/directory"}}}{"mcpServers":{"leonlesenechal-knocklog":{"serverUrl":"https://api.knocklog.ai/mcp/directory"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
Details
From the project READMEKnocklog API
The public description of the Knocklog API: analytics for AI agents. See which AI agents visit a website, whether each one is who it claims to be, what they read, and the visitors and leads AI assistants send.
- Docs: https://knocklog.ai/docs/api
- OpenAPI 3.1:
openapi.json, also served live at https://api.knocklog.ai/openapi.json - Base URL:
https://api.knocklog.ai
Quick start
# Check how a site treats AI agents (no key)
curl "https://api.knocklog.ai/v1/scan?domain=example.com"
# Identify one request
curl -X POST "https://api.knocklog.ai/v1/classify" -H "Content-Type: application/json" \
-d '{"user_agent": "Mozilla/5.0; compatible; GPTBot/1.4; +https://openai.com/gptbot", "ip": "20.171.206.10"}'
# Create a project: returns an ingest key, an admin key and install code
curl -X POST "https://api.knocklog.ai/v1/projects" -H "Content-Type: application/json" -d '{"domain": "example.com"}'
# Read the report
curl "https://api.knocklog.ai/v1/traffic?days=30" -H "Authorization: Bearer $KNOCKLOG_ADMIN_KEY"
The ingest key (kl_ing_…) only sends traffic and is safe in a collector on the site. The admin key (kl_adm_…) reads reports; keep it private. More in examples/.
Endpoints
| Endpoint | What it does | Key |
|---|---|---|
GET /v1/agents | List known AI agents | none |
POST /v1/classify | Identify and verify one request | none |
GET /v1/scan | Check how a site treats AI agents | none |
POST /v1/scan | Check how a site treats AI agents (JSON body) | none |
GET /v1/plans | List plans | none |
POST /v1/projects | Create a project | none |
POST /v1/events | Send requests from a collector | ingest (optional) |
POST /v1/logs | Import access logs | ingest |
GET /v1/plan | Plan and usage | ingest or admin |
GET /v1/traffic | Traffic report | admin |
GET /v1/account | Account overview | admin |
GET /v1/ready-files | Ready-made robots.txt and llms.txt (Pro) | admin |
POST /v1/keys/ingest | New ingest key | admin |
POST /v1/project/summary | Weekly summary by email | admin |
POST /v1/integrations | Webhook, Slack and company emails | admin |
POST /v1/install/cloudflare | Install the collector on Cloudflare | admin |
POST /v1/billing/checkout | Checkout link for a paid plan | admin |
POST /v1/billing/portal | Link to manage the subscription | admin |
GET /v1/badge/{project}.json | Badge status | none |
GET /v1/badge/{project}.svg | Badge image | none |
Webhooks: company.visited and lead.from_ai, signed with x-knocklog-signature (example).
For AI agents
The same features over the Model Context Protocol:
https://api.knocklog.ai/mcp/directory: public tools, no sign-inhttps://api.knocklog.ai/mcp/account: one project, OAuth sign-inhttps://api.knocklog.ai/mcp: every tool, keys as arguments
Listed in the official MCP Registry as io.github.leonlesenechal/knocklog.
Also from Knocklog
- knocklog/ai-agents: open directory of AI agents and crawlers (JSON, CSV)
Support
Questions or a missing endpoint: open an issue or write to [email protected]. Using the API is subject to the terms. The files in this repository are under the MIT license.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.