py-har-mcp
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TDQS
Scored across 7 tools
Each tool has a clear, distinct purpose: loading data, listing URL/method combos, filtering request IDs, fetching request details, aggregating by domain or status code, and searching content. No two tools overlap in function.
All tool names follow a consistent verb_noun pattern: load_har, list_urls_methods, get_request_ids, get_request_details, get_domain_stats, get_status_code_stats, search_har. The verbs are uniform and descriptive.
With 7 tools, the set is well-scoped for HAR analysis. Each tool covers a distinct aspect of the workflow, and the count is neither sparse nor bloated.
The surface covers the main HAR analysis workflow: load, browse, filter, inspect, search, and statistics. A minor gap is the absence of a direct 'get all requests' tool, but this can be worked around by combining list_urls_methods with get_request_ids.