Semble
Code search for agents that uses 98% fewer tokens than grep
Details
- External ID
- 47997629
- Source
- HN
- Company
- —
- Product
- Semble
- Website domain
- github.com
- Launched
- May 3, 2026
- Cohort
- —
- Upvotes
- 8
- Upvotes percentile
- 0.4894991922455573
- Tags
- —
- Fetched at
- Sept. 7, 2026, 9:26 p.m.
- Updated at
- Sept. 7, 2026, 9:26 p.m.
Description
Hey HN! We (Stephan and Thomas) recently open-sourced Semble. We kept running into the same problem while using Claude Code on large codebases: when the agent can't find something directly, it falls back to grep, reading full files or launching subagents. This uses a lot of tokens, and often still misses the relevant code. There are existing tools for this, but they were either too slow to index on demand, needed API keys, or had poor retrieval quality.So we built Semble. It combines static Model2Vec embeddings (using our latest static model: potion-code-16M) with BM25, fused via RRF and reranked with code-aware signals. Everything runs on CPU since there's no transformers involved. On our benchmark of ~1250 query/document pairs across 63 repos and 19 languages, it uses 98% fewer tokens than grep+read and reaches 99% of the retrieval quality of a 137M-parameter code-trained transformer, while being ~200x faster.Main features:- Token-efficient: 98% fewer tokens than grep+read- Fast: ~250ms to index a typical repo on our benchmark, ~1.5ms per query on CPU (very large repos may take longer)- Accurate: 0.854 NDCG@10, 99% of the best transformer setup we tested- MCP server: drop-in for Claude Code, Cursor, Codex, OpenCode- Zero config: no API keys, no GPU, no external servicesInstall in Claude Code with: claude mcp add semble -s user -- uvx --from "semble[mcp]" sembleOr check our README for other installation instructions, benchmarks, and methodology:Semble: https://github.com/MinishLab/sembleBenchmarks: https://github.com/MinishLab/semble/tree/main/benchmarksModel: https://huggingface.co/minishlab/potion-code-16MLet us know if you have any feedback or questions!
Enrichment
- Theme
- Claude integrations and coding agents
- Vertical
- Horizontal
- Function
- Search & retrieval
- Audience
- Developer
- AI stance
- AI-native
- Project type
- Commercial product
- Normalized one-liner
- code search for ai agents
- Manually corrected
- False
Could you build this?
Partial Building a simple AST or symbol indexer is accessible, but building a production-grade code search tool that reduces token usage by 98% compared to grep across huge codebases requires sophisticated code graph indexing, chunking, and ranking algorithms.
What it would actually take: A production tool needs a high-performance parser (such as tree-sitter bindings in Rust), symbol resolution algorithms, and efficient lexical/hybrid vector indexing. It must parse language constructs (functions, classes, references) and output compact, semantically dense summaries specifically formatted for LLM context windows. Deep systems engineering and compiler/parsing domain knowledge are required.
Discussion
No comments on this launch.
Competitors
Other products that read as similar to this one — 268 launches clear the similarity bar, closest 8 shown.
Attention rank: #152 of 269 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).
Launched 178 days after the earliest competitor.
- CodeRLM · hn · 2026-02-11 · 81 upvotes · similarity 0.53
- WarpGrep: A 20x faster subagent to grep for code · yc · 2025-11-28 · 17 upvotes · similarity 0.50
- Graft · hn · 2026-08-14 · 39 upvotes · similarity 0.50
- Maxxwell · hn · 2026-09-09 · 11 upvotes · similarity 0.47
- Edgee Claude Code Compressor V2 · ph · 2026-07-06 · 179 upvotes · similarity 0.47
- I nerfed our coding agents on purpose · hn · 2026-06-05 · 27 upvotes · similarity 0.45
- Agentmemory · ph · 2026-05-16 · 322 upvotes · similarity 0.45
- Abralo · hn · 2026-07-08 · 37 upvotes · similarity 0.45