Skills and MCP tagged “vector-database”

rag-implementation Seth Hobson skill This skill helps build RAG systems with vector search and LLM answers grounded in external documents. Use it for document Q&A and knowledge assistants. Claude Code CX Codex Cursor 13,906installs similarity-search-patterns Seth Hobson skill This skill helps build similarity search with vector databases for semantic search, RAG retrieval, nearest-neighbor queries, and hybrid search. Claude Code CX Codex Cursor 10,700installs rag-architect Alireza Rezvani skill Design a RAG pipeline around your documents, then measure retrieval quality. Use it to explore chunking strategies, embeddings, or vector databases. Claude Code 629installs qdrant-scaling official github skill Guides Qdrant scaling decisions across data volume, query throughput, latency, and result payload sizes. GitHub Copilot 61installs qdrant-deployment-options official github skill Guides the choice between Qdrant deployment types based on latency, operational overhead, and data residency needs. GitHub Copilot 61installs qdrant-clients-sdk official github skill This skill guides Qdrant integration through official SDKs and APIs. Use it when building with Python, TypeScript, Rust, Go, .NET, or Java. GitHub Copilot 61installs qdrant-version-upgrade official github skill Provides rules for upgrading Qdrant and its SDK without downtime or data corruption. Helps plan rolling cluster upgrades and multi-version storage migrations. GitHub Copilot 59installs pinecone-rag official github skill This skill guides Pinecone-based RAG pipelines and persistent agent memory. Use it for semantic document search, hybrid retrieval, or context shared across sessions. GitHub Copilot 24installs