Extracts code symbols like functions, classes, and structs from codebases with surgical precision for AI assistants.
Sponsored
Traditional AI assistants often consume entire codebases as plain text, leading to massive token consumption and irrelevant context. FS Query revolutionizes this by acting as a Model Context Protocol (MCP) server, leveraging Tree-sitter to surgically extract specific code symbols such as functions, classes, and variables. This allows AI assistants to understand code structure, query for precise information, and dramatically reduce token usage, making interactions more efficient and relevant.
主な機能
011 GitHub stars
02Model Context Protocol (MCP) server integration for AI assistants
03Precise code symbol extraction using Tree-sitter parsing
04Supports multiple programming languages including Rust, Python, C++, JavaScript/TypeScript, and Go
05Filters extracted symbols by type (functions, classes, structs, variables, enums, traits/interfaces)
06Command-line interface (CLI) for standalone code analysis and symbol extraction
ユースケース
01Enabling AI assistants to query specific code elements (e.g., 'Show me all classes') without full file ingestion.
02Providing AI with precise context about functions, variables, or structs to answer coding questions efficiently.
03Reducing token consumption and improving relevance for AI assistants interacting with codebases.
