semble
Reduces token consumption and latency in agentic code navigation, lowering API costs and enabling faster iteration loops for large codebases without sacrific…
Code search built for agents: indexes an average repo in about 250 ms and answers queries in about 1.5 ms, entirely on CPU with no API keys, GPU, or external services. Returns only the relevant code chunks — the project benchmarks ~98% fewer tokens than grep-plus-read at 99% of a code transformer's retrieval quality. Integrates with Claude Code, Cursor, Codex, and OpenCode as an MCP server, a CLI documented in AGENTS.md, or a dedicated semble-search sub-agent; works on local paths or git URLs.
- Find specific function definitions across large codebases without reading entire files.
- Locate all usages of a deprecated API to plan migration work efficiently.
- Search for error handling patterns to audit consistency across your codebase.
Reduces token consumption and latency in agentic code navigation, lowering API costs and enabling faster iteration loops for large codebases without sacrificing search accuracy.
Teams deploying AI agents on code tasks who need efficient codebase indexing and retrieval.
https://github.com/MinishLab/semble
By MinishLab
How to Get It
uv tool install semble && semble install
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
After installing, paste this into Claude:
Help me find specific function definitions across large codebases without reading entire files
Trust Signals Auto-scanned
Community Pulse Growing
Discussed on Hacker News, Reddit
- Show HN: Semble – Code search for agents that uses 98% fewer tokens than grep — Hacker News · 442 pts
- Semble: code search MCP for OpenCode that matches transformer accuracy on CPU — Reddit · 25 pts
- Show HN: Semble – Code search for agents that uses 98% fewer tokens than grep — Hacker News · 8 pts
3 mentions across 2 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 3,649 GitHub stars; contributors unknown; last commit 0d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
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Evaluation
Scored from trust signals (evidence-eval-v1): 3,649 GitHub stars; contributors unknown; last commit 0d ago; license MIT.