MCP Server2026
Provides a local MCP server that returns precise, symbol-level code (functions, classes, imports) via tree-sitter parsing so AI agents send only the bytes they need—commonly cutting code-reading token usage 95%+ and enabling compact packed responses for further savings.
Measures how well LLMs and agent-driven workflows prepare supervised training data end-to-end by jointly benchmarking data construction and data-quality evaluation across six domains, using a downstream-grounded protocol and new metrics.