A
licenseA
qualityC
maintenanceAn AST-based MCP server that provides token-efficient codebase skeletons to LLM agents, reducing context token usage by 80-95% by exposing structural information instead of full source files.
5
4 npm
3
MIT
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Scored across 4 tools
Each tool has a clear, distinct purpose: freeing cache, compressing error logs, reading structural skeletons, and expanding function bodies. No overlap in functionality.
All tools follow a consistent verb_noun snake_case pattern, e.g., context_gc, parse_error_log, read_code_skeleton, read_function_body. Predictable and clear.
Four tools is well-scoped for a server focused on context optimization. Each tool earns its place with a specific function, not too few or too many.
The tool set covers the key strategies: triggering GC, compressing errors, reading skeletons, and expanding functions. Minor gaps like clearing specific caches exist but do not hinder typical workflows.