cgrep: Code-Aware Search Tool for AI Coding Agents

cgrep is a code-aware search tool designed to improve the efficiency of AI coding agents. It combines full-text search with AST symbol extraction and optional semantic search, providing a comprehensive approach to code understanding. Benchmarks on PyTorch show significant improvements in token usage and retrieval latency compared to traditional grep workflows. cgrep's deterministic JSON output facilitates seamless integration with AI agent workflows, while its local-first design ensures speed and privacy. The tool offers various features, including definition, reference, and caller search, as well as ergonomic CLI shortcuts. It also supports indexing, watch/daemon, and MCP server mode for scaling on large repositories. The measured improvements on February 14, 2026, across six AI-coding scenarios, demonstrate cgrep's potential to enhance AI-assisted coding. cgrep used only 4.8% of the token volume of a plain grep workflow.

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