13건 · 관련도순
Search Apple Notes by meaning or exact text, discover related notes and unexpected connections, and synthesize ideas with citations. The skill guides local setup and tool selection, with on-device search and optional local or cloud language models for synthesis.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Search arXiv physics, math, and computer science preprints using natural language queries. Powered by Valyu semantic search.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use this skill for setting up vector similarity search with pgvector for AI/ML embeddings, RAG applications, or semantic search. **Trigger when user asks to:** - Store or search vector embeddings in PostgreSQL - Set up semantic search, similarity search, or nearest neighbor search - Create HNSW or IVFFlat indexes for vectors - Implement RAG (Retrieval Augmented Generation) with PostgreSQL - Optimize pgvector performance, recall, or memory usage - Use binary quantization for large vector datasets **Keywords:** pgvector, embeddings, semantic search, vector similarity, HNSW, IVFFlat, halfvec, cosine distance, nearest neighbor, RAG, LLM, AI search Covers: halfvec storage, HNSW index configuration (m, ef_construction, ef_search), quantization strategies, filtered search, bulk loading, and performance tuning.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
小遥搜索 MCP 工具 - 本地文件智能搜索（语义/全文/图像/语音/混合搜索）
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Semantic search in the DDC CWICR construction cost database using vector embeddings (BGE-M3, 1024-dim, per-language Qdrant collections). Find similar work items and resources for cost estimation across 8 national bases and 30 markets in 26 languages.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Semantic + keyword search and connection-discovery across the user's own Apple Notes via the apple-notes MCP server. Use when the user wants to find, recall, or synthesize something from their notes, or surface non-obvious bridges/related notes. macOS, on-device.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Serverless vector database at the edge with Cloudflare Vectorize. Use when: building semantic search on Cloudflare Workers, RAG pipelines at the edge, low-latency vector similarity search, or storing and querying embeddings without managing a separate vector database.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Assists with storing, searching, and managing vector embeddings using ChromaDB. Use when building RAG pipelines, semantic search engines, or recommendation systems. Trigger words: chromadb, chroma, vector database, embeddings, semantic search, similarity search, vector store, rag.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Semantic code search using Phase 1 vector embeddings and Phase 2 hybrid search.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Search PubMed biomedical literature with natural language queries powered by Valyu semantic search. Full-text access, integrate into your AI projects.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Semantic + keyword search and connection-discovery across the user's own Apple Notes via the apple-notes MCP server. Use when the user wants to find, recall, or synthesize something from their notes, or surface non-obvious bridges/related notes. macOS, on-device.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Search arXiv physics, math, and computer science preprints using natural language queries. Powered by Valyu semantic search.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Semantic + keyword search and connection-discovery across the user's own Apple Notes via the apple-notes MCP server. Use when the user wants to find, recall, or synthesize something from their notes, or surface non-obvious bridges/related notes. macOS, on-device.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.