mgrep-code-search

Semantic code search uses natural language queries to locate implementations and understand intent, returning precise file references and context. Unlike traditional grep, it captures relationships between components in large or nested repositories where context is missed.

To search a large codebase semantically, index the repository files using a watcher that respects .gitignore, then query the index with natural language to quickly identify relevant code and file references across nested directory structures.

Semantic code search supports large or nested repositories by indexing files through a watcher workflow. The watcher respects .gitignore rules and hidden files, keeping the searchable index current and accurate for natural language queries.

Yes, you can use natural language queries to semantically search a codebase and understand implementation intent. The search tool queries a maintained index to return precise file references and relevant context without requiring manual inspection.

The best way to locate code without manual inspection is using semantic code search. It requires a watcher to index the repository files and a semantic search tool to query the index, yielding relevant code and context from natural language inputs.

Traditional grep misses context because it relies on exact string matching without understanding structure or relationships between components. Semantic code search overcomes this by indexing file context and intent for natural language retrieval.