Technology & Engineering8 skills

Vector Db Services skills for AI agents

8 practitioner-grade vector db services skills, each a focused Markdown document your agent loads into context on demand. Search them from Claude Desktop, Cursor or any MCP client, or pull one with the CLI.

$ npx skilldb search "vector db services"

All 8 skills

Chromadb
Integrate with ChromaDB open-source embedding database for local and persistent vector storage. Guide collection management, document add/query operations, metadata filtering, and embedding function configuration using the ChromaDB TypeScript client.
179 lines
Langchain
Build LLM-powered applications using the LangChain TypeScript framework. Guide chain composition, agent creation, tool integration, memory management, retriever configuration, and callback instrumentation using LangChain.js.
197 lines
Llamaindex
Build data-augmented LLM applications using the LlamaIndex TypeScript framework. Guide index construction, query engine configuration, retriever customization, chat engine setup, and data connector usage via LlamaIndex.TS.
170 lines
Pgvector
Integrate pgvector PostgreSQL extension for vector similarity search within an existing Postgres database. Guide vector column setup, IVFFlat and HNSW index creation, hybrid SQL-plus-vector queries, and performance tuning using TypeScript with node-postgres or Drizzle ORM.
172 lines
Pinecone
Integrate with Pinecone vector database for similarity search at scale. Guide index creation, vector upsert/query operations, metadata filtering, and namespace partitioning using the official Pinecone TypeScript client.
149 lines
Qdrant
Integrate with Qdrant vector similarity search engine for high-performance nearest-neighbor retrieval. Guide collection setup, point operations, payload filtering, snapshot management, and advanced indexing via the Qdrant JS client.
175 lines
Vercel AI SDK
Build AI-powered applications using the Vercel AI SDK for streaming chat, text completion, and tool calling. Guide useChat/useCompletion hook usage, server-side streaming, structured output, provider configuration, and multi-step tool execution in Next.js and Node.js applications.
200 lines
Weaviate
Integrate with Weaviate vector search engine for semantic and hybrid search. Guide collection schema design, vectorizer configuration, hybrid search queries, and generative module usage via the official Weaviate TypeScript client v3.
165 lines