An MCP server for efficient code indexing and symbol retrieval using tree-sitter AST parsing to fetch specific functions or classes without loading entire files. It significantly reduces AI token costs by providing O(1) byte-offset access to code components across multiple programming languages.
An MCP server that provides ultra-efficient code exploration through AST analysis, reducing LLM token usage by up to 95% while enabling instant call graph generation and dependency analysis for massive codebases.
A persistent, tree-sitter-backed code knowledge cache MCP server that reduces token usage by storing parsed structure and enabling fast symbol lookup, inheritance graph, call graph, and semantic search.
Token-efficient code intelligence MCP server that indexes codebases with tree-sitter AST parsing and provides 150 tools for AI agents, using 61-95% fewer tokens than traditional grep/Read workflows.
Token-efficient MCP server for multi-language project analysis (Java, TypeScript, JavaScript, Markdown, Python) with plugins, semantic search, and static analysis.
An MCP server that provides structure-aware code analysis (symbol trees, dependencies, docs) to reduce AI agent token consumption by up to 99%, along with Git commit intelligence.
