Semble: A CPU-Based Code Search Library for AI Agents That Reduces Token Usage by 98%
By
Bibabomas
A baker's-dozen of insight crammed into one ring.
Summary
Semble is a code search library designed for AI agents that enables fast and accurate code retrieval using ~98% fewer tokens than traditional grep+read approaches. It indexes and searches entire codebases in under a second, with ~200x faster indexing and ~10x faster queries compared to code-specialized transformers, while maintaining 99% of retrieval quality. The tool runs entirely on CPU with no need for API keys, GPUs, or external services, and can be used as an MCP server or via shell integration with agents like Claude Code, Cursor, Codex, and OpenCode.
Key quotes
· 4 pulledSemble is a code search library built for agents. It returns the exact code snippets they need instantly, using ~98% fewer tokens than grep+read.
Indexing and searching a full codebase end-to-end takes under a second, with ~200x faster indexing and ~10x faster queries than a code-specialized transformer, at 99% of its retrieval quality.
Everything runs on CPU with no API keys, GPU, or external services.
Run it as an MCP server or call it from the shell via AGENTS.md and any agent (Claude Code, Cursor, Codex, OpenCode, etc.) gets instant access to any repo.
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