Alternatives
Products that do what Sqry – semantic code search using AST and call graphs does
I built sqry, a local code search tool that works at the semantic level rather than the text level. The motivation: ripgrep is great for finding strings, but it can't tell you "who calls this function", "what does this function call", or "find all public async functions that return Result". Those questions require understanding code structure, not just matching patterns. sqry parses your code into an AST using tree-sitter, builds a unified call/ import/dependency graph, and lets you query it: sqry query "callers:authenticate" sqry query "kind:function AND visibility:public AND…
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Codemod grep searches public code by syntax and structure, not just text or regex. Use ast-grep patterns to find code by shape across repositories.
15d ago · grep.codemod.com
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For the past couple of months, I’ve been building a tool that enables natural language search over large codebases using Tree-Sitter for syntax parsing and Qdrant for vector-based retrieval. https://app.repogram.com ### How It Works - Tree-Sitter is used to parse syntax trees and extract high-quality vector embeddings of code. - These embeddings are stored in Qdrant, enabling fast similarity search across your entire repo. - A combination of re-ranking processes refine search results, producing highly relevant answers to code-related questions. The results have been incredibly…
2025 · app.repogram.com
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I built this because I got tired of watching Claude Code read through massive files just to find a few functions. Sourcerer lets AI agents search code semantically and grab exactly the code chunks they need instead of burning tokens on whole files. It uses tree-sitter to parse your codebase and creates a searchable index. So instead of "read auth.py (538 lines)", an agent can search for "user authentication logic" and get back just the relevant functions. Demo: https://asciinema.org/a/736638 GitHub: https://github.com/st3v3nmw/sourcerer-mcp
2025 · github.com
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You write a standard solution, just like on LeetCode, and run it through the CLI. It identifies the problem by ID or title, executes your code against local test cases, and shows the result. It currently supports around 1.4k problems and multiple languages, including Python, C++, Rust, Java, Go, TypeScript, Swift, and others. The project is still an MVP. System design, SQL, and concurrency problems are not supported yet, but support for more problem types is planned. Made in Haskell!
19d ago · github.com
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Hi HN, I built XRAY MCP after discovering that AI assistants were scanning my projects with plain grep and guessing. I tried direct tree-sitter integration and language servers; both felt heavy for a lightweight tool. ast-grep hit a sweet spot: syntax-aware search in a single binary. XRAY MCP wraps it behind three endpoints—map, find, impact—so a model (or human) can answer questions like “what breaks if I change this function?” on demand. It’s stateless, supports Python/JS/TS/Go, and installs quickly. Repo: https://github.com/srijanshukla18/xray Would love…
2025 · github.com
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Hey folks, I just wanted to share a quick script I threw together called notational ls. One of the big problems of any code base (or any filesystem) is that it's hard to tell what's what - folder and file names often trade brevity for clarity. So I thought about a version of `ls` that works like this: > nls web: Where python web server files are stored ad_hoc: One time scripts ios: Our IOS code images Adding descriptions is really easy too: > nls images Images SHARED between both ios and web web: Where python web server files are stored ad_hoc: One time scripts ios: Our IOS code…
2011
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I built a library that lets you find code patterns using familiar CSS-like selectors, then connected it to Claude via MCP so AI assistants can understand and refactor codebases. The Approach // Find code patterns with intuitive selectors: const asyncFunctions = tree.findAll('function[async]'); const todoComments = tree.findAll('comment[text="TODO"]'); const reactHooks = tree.hooks(); // Built-in React support // Chain smart transformations: tree.transform() .rename('oldFunction', 'newFunction') .removeUnusedImports() .toString(); Key Features - CSS-like…
2025
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Built QueryWeaver, an open-source text2SQL tool that uses a graph to create a semantic layer on top of your existing databases. When you ask "show me customers who bought product X in a certain ‘REGION’ over the last Y period of time," it knows which tables to join and how. When you follow up with "just the ones from Europe," it remembers what you were talking about. Instead of feeding the model a list of tables and columns, we feed it a graph that understands what a customer is, how it connects to orders, which products belong to a campaign, and what "active user" actually means in your…
2025 · github.com
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Hello Hacker News! I built Sleuth, an open source search tool for your workspace. I originally started off with Slack but quickly learned that Confluence search is a well documented problem: https://twitter.com/beajammingh/status/1273742155731791872?s... Sleuth solves this problem using semantic search to find relevant Confluence pages and Slack messages for your query. You can ask Sleuth questions about HR policies, technical documentation, product decisions, and more. Sleuth is open source and can be self-hosted, although there are dependencies on OpenAI and…
2023 · github.com
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Hi HN, I built ast-visualizer.com because I wanted a way to visualize the architecture/structure of a Python repo before dived into the code. Most tools tell you what the code does; I wanted to see how it's built. The Problem: Onboarding onto a large codebase is a nightmare. LLMs help with single functions, but they struggle to show you the "God Objects," circular dependencies, or high-complexity hotspots across 50+ files. What it does: Dependency Graph: Visualizes imports and file complexity to find architectural bottlenecks. Radial AST Heatmaps: Maps individual files and color-codes…
Feb 2026 · ast-visualizer.com
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2020 · codesnippetsearch.net
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OP here. I built RepoReaper to solve code context fragmentation in RAG. Unlike standard chat-with-repo tools, it simulates a senior engineer's workflow: it parses Python AST for logic-aware chunking, uses a ReAct loop to JIT-fetch missing file dependencies from GitHub, and employs hybrid search (BM25+Vector). It also generates Mermaid diagrams for architecture visualization. The backend is fully async and persists state via ChromaDB. Link: https://github.com/tzzp1224/RepoReaper
Jan 2026 · github.com
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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…
May 2026 · github.com
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Releasing ColGREP today, made using our open-source multi-vector database, it support grep like filtering while adding an extra input to rank output of grep based on semantic similarity. ColGREP is packed with strong code retrieval models we designed and run 100% locally.
Feb 2026 · github.com
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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…
2023 · usearch-images.com
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hi hn, today I'm open sourcing a new SQL-like query language that's built for the web. it has dedicated syntax for request, parsers, selectors, and javascript snippets... it was built on nodejs with the incredible moo lexer and nearley parser. if you're a fan of regular expressions, do I have some code to show you! the website is mostly just a few examples and a playground where you can write & run (& share!) your own queries. there's also an introductory blog post where i try but ultimately fail to justify why this should be its own language and not a library/framework. enjoy!
2024 · getlang.dev
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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…
Apr 2026 · github.com
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Hi there! We built a Bing-chat-like conversational search engine with less than 500 lines of python code (and a similar amount of frontend script). The source code is fully open-source at https://github.com/leptonai/search_with_lepton , and we put up a live demo at https://search.lepton.run/. Let us know what you think!
2024 · search.lepton.run
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Hi, Please check out my new library funcy. It's really simplified AWS Lambda APIs in my projects, so I thought I would open-source it. It strongly-types all request parameters, has support for CORS, content-negotiation, security headers, etc.. out of the box and works via a very simply declarative interface with progressive disclosure. It's currently pre-release, let me know what you think :)
2024 · github.com
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2019 · github.com
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