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Monitor and capture JSON network responses from web pages using Playwright, with ML-based endpoint classification and MCP server integration
netjsonmon provides 6 tools with complete input schemas and descriptions. Naming follows verb_noun convention (capture_json_responses, inspect_capture, filter_endpoints, label_endpoints, train_classifier, initialize_project). Descriptions are present and substantive (100-200 chars typical). However, output schemas are not documented in the source code, LLMs cannot predict return structures. Parameter descriptions are good but some lack format/constraint details (e.g., minScore/maxScore accept strings but no validation guidance). Error handling is minimal, no recovery guidance or actionable error messages visible. Tool composition is sound (each does one thing), but no pagination or result-limiting patterns evident in inspect_capture or filter_endpoints despite potentially large result sets.
Capture JSON network responses from a URL by running a browser session with configurable monitoring duration, timeout, filtering, and output options
Filter, sort, and export endpoints from a capture by score, host, method, path, and other criteria
Create configuration file and example flow for a new netjsonmon project
View capture summary and endpoint details from a completed capture directory
Manually label endpoints as data or non-data and export training data for ML model training
Train ML classifier on labeled endpoints to identify data vs non-data endpoints
Output schemas not documented. LLMs cannot predict return structures for any tool. inspect_capture, filter_endpoints, and train_classifier return complex nested objects (capture summaries, endpoint lists, model metadata) but no schema is visible in source.
No error handling guidance. Tools lack recovery hints. E.g., if capture_json_responses times out or if filter_endpoints finds no matches, LLM receives no actionable next steps.
Parameter constraints not fully specified. minScore/maxScore in filter_endpoints are strings but should be numbers with range 0-1. No validation guidance in descriptions.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | D | 57 | 2026-07-28+ | v2 |
No pagination or result-limiting patterns. inspect_capture and filter_endpoints could return large result sets (all endpoints in a capture) without limit or cursor support, risking context window exhaustion.
Destructive operations lack confirmation. label_endpoints and train_classifier modify state (write labels, train models) but no dry-run or confirmation step is visible.