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SIFS
Extremely fast hybrid code search for agents.
Coding agents waste too much context before they understand a repo. They grep around the codebase, read large chunks, and make guesses. SIFS gives them fast local search. It runs as a CLI or MCP server. The default mode is hybrid search: BM25/semantic retrieval. Current benchmark: 63 large repos 19 languages 1,251 annotated search tasks index: 6.5 ms search: 0.376 ms SIFS is ahead of any comparable tool on this benchmark. Very open to feedback and issues/PRs! Let me know if you try it.
Top comment
I’ve been building SIFS, a Rust CLI/library/MCP server for local code search. The use case is coding agents. Before an agent reads half a repository, I want it to be able to ask rough questions like “where is authentication handled?” or “how does upload backpressure work?” and get ranked code chunks back. SIFS supports BM25, semantic search, and a hybrid mode. BM25 is fully offline and model-free. Semantic/hybrid search run locally once the model is cached. I’d especially like feedback on: - ranking failures - benchmark methodology - Rust API ergonomics - MCP interface design
About SIFS on Product Hunt
“Extremely fast hybrid code search for agents.”
SIFS was submitted on Product Hunt and earned 1 upvotes and 1 comments, placing #154 on the daily leaderboard. Coding agents waste too much context before they understand a repo. They grep around the codebase, read large chunks, and make guesses. SIFS gives them fast local search. It runs as a CLI or MCP server. The default mode is hybrid search: BM25/semantic retrieval. Current benchmark: 63 large repos 19 languages 1,251 annotated search tasks index: 6.5 ms search: 0.376 ms SIFS is ahead of any comparable tool on this benchmark. Very open to feedback and issues/PRs! Let me know if you try it.
On the analytics side, SIFS competes within Developer Tools and GitHub — topics that collectively have 553.8k followers on Product Hunt. The dashboard above tracks how SIFS performed against the three products that launched closest to it on the same day.
Who hunted SIFS?
SIFS was hunted by Tristan Manchester. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of SIFS including community comment highlights and product details, visit the product overview.