Refactor code snippets by applying specific instructions, using optional file context for precision. Supports multiple programming languages to enhance code quality and maintainability.
Retrieve cached code context for a specified file path to optimize AI assistant token usage. Supports TypeScript, JavaScript, Python, Go, and Rust with minimal, relevant context extraction.
Map compiled JavaScript code positions to original source code context using source maps, helping developers locate and fix issues by providing surrounding code lines.
Parse source files using AST to extract targeted code context and relevant imports, optimizing token usage for AI-based code analysis and assistance. Supports TypeScript, JavaScript, Python, Go, and Rust.
Provides code context and analysis for AI assistants by extracting directory structures and code symbols using WebAssembly Tree-sitter parsers with zero native dependencies.
Provides intelligent code context management and semantic search capabilities for software development, enabling natural language queries to find relevant code snippets, functions, and classes across Python, JavaScript, TypeScript, and SQL codebases.
An MCP server that provides semantic search over local git repositories, enabling users to clone repositories, process branches, and search code through vectorized code chunks.