search▌

When searching code, use this decision tree:

Fast, AI-powered codebase search using WarpGrep. 20x faster than traditional grep.

Search across all major biomedical databases (PubMed, bioRxiv, medRxiv, ClinicalTrials.gov, FDA drug labels) simultaneously using natural language queries powered by Valyu's semantic search API.

mgrep is a semantic search tool that enables natural language queries across code, text, PDFs, and images. It is particularly effective for exploring larger or complex codebases where traditional pattern matching falls short.

Category: provider

在使用此技能之前，请确保已安装必要的依赖包：

Expert patterns for Algolia search implementation, indexing strategies, and React InstantSearch integration. \n \n React InstantSearch with hooks (useSearchBox, useHits, useRefinementList, usePagination) for type-ahead search and faceted filtering in modern React applications \n Next.js SSR support via react-instantsearch-nextjs, compatible with both Pages Router and App Router, with URL synchronization and dynamic rendering configuration \n Three indexing strategies: full reindexing, full recor

Semantic code search by meaning rather than exact text strings. \n \n Searches code by intent and concept similarity using embeddings, returning ranked results with relevance scores (0.0–1.0) \n Requires GrepAI initialization, an active index created via grepai watch , and a running embedding provider like Ollama \n Supports natural language queries describing behavior or intent; 3–7 word phrases work best, with results limited via --limit flag \n Interprets scores: 0.90+ excellent match, 0.80–0

Search GitHub code, repositories, issues, and pull requests with flexible filtering. \n \n Four search types: code, repositories, issues, and pull requests, each with full GitHub search syntax support \n Optional filtering by repository owner and name to narrow results to specific projects \n Requires GitHub personal access token configured in mcp_config.json for authentication \n Command-line interface with straightforward parameters for integration into agent workflows \n

Rust-powered vector database for production RAG with hybrid search and distributed scaling. \n \n Supports dense, sparse, and multi-vector storage per point with four distance metrics (COSINE, EUCLID, DOT, MANHATTAN) and HNSW indexing for fast nearest-neighbor search \n Rich filtering during search across any payload field, with optional payload indexing for performance and support for complex boolean queries \n Quantization options (scalar, product, binary) and on-disk storage for memory effici