Semble – Fast code search for agents with near-transformer accuracy
Hey HN! We've just open-sourced Semble, a fast and accurate code search library built for agents. We're also releasing potion-code-16M, a small code-specialized static embedding model that powers it. Most embedding-based code search methods are either too slow to index on demand or need GPU infrastructure, while grep-style retrieval methods often cannot find the relevant content. Semble combines the speed and quality benefits of both, so agents waste less time and fewer tokens exploring. Main features: - Fast: indexes a full codebase in ~250 ms and answers queries in ~1.5 ms, all on CPU…
What it does
In the maker’s words, at launch
Hey HN! We've just open-sourced Semble, a fast and accurate code search library built for agents. We're also releasing potion-code-16M, a small code-specialized static embedding model that powers it. Most embedding-based code search methods are either too slow to index on demand or need GPU infrastructure, while grep-style retrieval methods often cannot find the relevant content. Semble combines the speed and quality benefits of both, so agents waste less time and fewer tokens exploring. Main features: - Fast: indexes a full codebase in ~250 ms and answers queries in ~1.5 ms, all on CPU (roughly ~200x faster indexing and ~10x faster queries than a code-specialized transformer). - Accurate: on par with code-specialized transformer models at a fraction of the size (see our benchmarks for more info). - MCP server: drop-in tool for Claude Code, Cursor, Codex, OpenCode, and any other MCP-compatible CLI/agent. Repos are cloned and indexed on demand. - Zero setup: runs on CPU with no API keys, GPU, or external services. Install as an MCP server for Claude Code: claude mcp add semble -s user -- uvx --from "semble[mcp]" semble Or check our README for install instructions for Codex, OpenCode, Cursor, and other agents. Semble: https://github.com/MinishLab/semble Benchmarks: https://github.com/MinishLab/semble/tree/main/benchmarks How it works: https://github.com/MinishLab/semble#how-it-works Model: https://huggingface.co/minishlab/potion-code-16M
Does the same job
all alternatives →- SCSemble – Code search for agents that uses 98% fewer tokens than grepMay 2026 · github.com · ▲8
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…
- BCBuilding code agents? Try code embedding models FAST and do it better2025 · ▲8
We are a small group of undergrads interested in building human in the loop coding agents. We dream of a world where building complex agent workflows feels as simple and creative as playing with legos. When we were building stuff we needed a tool that made it easy to try out different code embedding models so that we could see which ones worked best in different scenarios and understand their strengths and weaknesses. So to speed that process up we made PurpleSearch an 'instant' search engine for your local codebases. This tool lets you quickly deploy any open source embedding model on…
- AEAn experimental code search engine2018 · codegrep.com · ▲88
- RBRust Based Per-Token Late Interaction Dense Search2025 · github.com · ▲8
Happy to release FastPlaid, which aim to ease and accelerate ColBERT and ColPali retrieval
- UIUSearch Images demo in 200 lines of Python2023 · usearch-images.com · ▲9
Hey everyone! I am excited to share updates on four of my & my teams' open-source projects that take large-scale search systems to the next level: USearch, UForm, UCall, and StringZilla. These projects are designed to work seamlessly together, end-to-end—covering everything from indexing and AI to storage and networking. And yeah, they're optimized for x86 AVX2/512 and Arm NEON/SVE hardware. USearch [1]: Think of it as Meta FAISS on steroids. It's now quicker, supports clustering of any granularity, and offers multi-index lookups. Plus, it's got more native bindings than probably…
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With social media and now AI, its important to keep the indie web alive. There are many people who write frequently. Blogosphere tries to highlight them by fetching the recent posts from personal blogs across many categories. There are two versions: Minimal (HN-inspired, fast, static): https://text.blogosphere.app/ Non-minimal: https://blogosphere.app/ If you don't find your blog (or your favorite ones), please add them. I will review and approve it.
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