An MCP server that provides semantic code intelligence by pre-indexing codebases, enabling AI agents to query symbol relationships and code structure directly, reducing costs and tool calls.
Intelligent code indexing MCP server that saves 99% of tokens by retrieving exact function source via byte-offset seek. Provides 15 tools for symbol search, call graphs, and incremental indexing across 10 languages.
An MCP server that provides structural codebase indexing and surgical query tools to drastically reduce token usage through symbol-level searches and transitive impact analysis. It supports multiple languages and integrates with git to help AI agents understand code dependencies and the impact of changes in sub-millisecond time.
A token-efficient MCP server for exploring GitHub repositories using tree-sitter AST parsing to extract symbol signatures and summaries. It enables users to search and retrieve specific code components while significantly reducing token consumption compared to raw file dumps.
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.
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.