# Vector Database > Browse 22 items tagged with Vector Database. ## Items - [Claude Context with LanceDB](https://mcpserver.ever.works/items/claude-context-with-lancedb) — AI-powered semantic code search Model Context Protocol server using LanceDB local vector database with zero-config setup, optional Milvus/Zilliz Cloud support for enterprise semantic code navigation. - [Vectara RAG MCP Server](https://mcpserver.ever.works/items/vectara-rag-mcp-server) — Vectara-MCP provides agentic applications with fast, reliable RAG through the Model Context Protocol. Leverages Vectara's Trusted RAG platform with semantic search, hallucination detection, and grounded generation capabilities. - [Pinecone MCP Server](https://mcpserver.ever.works/items/pinecone-mcp-server) — MCP server built on Pinecone’s vector database for fast, similarity-based context retrieval optimized for LLMs recalling semantically relevant facts or documents. - [MCP Server Qdrant](https://mcpserver.ever.works/items/mcp-server-qdrant) — A Qdrant MCP server for vector database interactions. Apache-2 licensed. - [LlamaCloud MCP Server](https://mcpserver.ever.works/items/llamacloud-mcp-server) — LlamaCloud MCP Server enables AI agents to perform natural-language queries over managed vector indexes. Ideal for RAG and orchestration in agentic workflows with persistent vector storage. - [chroma-mcp](https://mcpserver.ever.works/items/chroma-mcp) — A server providing data retrieval capabilities powered by the Chroma embedding database, enabling AI models to create and retrieve data collections using vector search, full text search, and metadata filtering. - [Chroma MCP Server (privetin)](https://mcpserver.ever.works/items/chroma-mcp-server-privetin) — MCP server implementation providing vector database capabilities through Chroma, enabling LLMs to store, query, and manage vector embeddings for retrieval-augmented generation workflows. - [Qdrant MCP Server for Semantic Search](https://mcpserver.ever.works/items/qdrant-mcp-server-for-semantic-search) — Model Context Protocol server providing semantic search capabilities using local Qdrant vector database with support for multiple embedding providers including Ollama, OpenAI, Cohere, and Voyage AI for intelligent information retrieval. - [Qdrant MCP Server](https://mcpserver.ever.works/items/qdrant-mcp-server-qdrant) — Qdrant MCP server for vector similarity search and storage. Features high-performance vector database with semantic search, filtering, and recommendations. Ideal for AI/ML applications requiring fast vector operations. - [Chroma MCP Server](https://mcpserver.ever.works/items/chroma-mcp-server) — A Model Context Protocol server implementation that provides database capabilities for Chroma, enabling AI assistants to interact with Chroma vector databases for embeddings and semantic similarity. - [Qdrant MCP Server](https://mcpserver.ever.works/items/qdrant-mcp-server) — Qdrant MCP Server integrates Qdrant's vector database with MCP for semantic search and similarity matching in AI workflows. It supports vector embeddings, collections management, and hybrid search combining dense and sparse vectors. Ideal for RAG pipelines, recommendation systems, and knowledge retrieval in agents; offers an open-source, self-hosted alternative to Pinecone MCP. - [LanceDB MCP Server (Node.js)](https://mcpserver.ever.works/items/lancedb-mcp-server-nodejs) — Node.js-based LanceDB MCP Server providing vector database capabilities through LanceDB's serverless vector database. - [MCP Pinecone Server](https://mcpserver.ever.works/items/mcp-pinecone-server) — Model Context Protocol server enabling reading and writing from Pinecone vector database, providing basic RAG (Retrieval-Augmented Generation) capabilities for LLM applications. - [MCP Server Milvus](https://mcpserver.ever.works/items/mcp-server-milvus) — Model Context Protocol Servers for Milvus vector database, enabling vector similarity search and data management operations. - [MCP Server Milvus (zilliztech)](https://mcpserver.ever.works/items/mcp-server-milvus-zilliztech) — Model Context Protocol Servers for Milvus by Zilliz, enabling LLMs to interact with Milvus vector database for vector similarity search and data management. - [Milvus](https://mcpserver.ever.works/items/milvus) — MCP server for searching, querying, and interacting with data in Milvus Vector Database, enabling AI agents to perform vector similarity searches. - [Pinecone](https://mcpserver.ever.works/items/pinecone) — Pinecone's developer MCP Server assisting developers in searching documentation and managing data within their development environment through vector database operations. - [VikingDB MCP Server](https://mcpserver.ever.works/items/vikingdb-mcp-server) — MCP server for VikingDB store and search, enabling vector database operations through Model Context Protocol. - [YouTube AI MCP Server](https://mcpserver.ever.works/items/youtube-ai-mcp-server) — An AI-powered YouTube solution that enables users to search for videos, retrieve detailed transcripts, and perform semantic searches over video content without relying on the official YouTube API, using vector database integration for streamlined content discovery. - [Zilliz Milvus MCP Server](https://mcpserver.ever.works/items/zilliztech-milvus-mcp) — Model Context Protocol Servers for Milvus vector databases by zilliztech. Enables LLMs to interact with Milvus for semantic search, similarity matching, and vector database operations through MCP. - [LanceDB MCP Server](https://mcpserver.ever.works/items/lancedb-mcp-server) — Embedded vector database MCP server providing local, zero-config vector storage and similarity search operations using LanceDB for efficient semantic search and AI-powered applications. - [Milvus MCP Server](https://mcpserver.ever.works/items/milvus-mcp-server) — Official Model Context Protocol server for Milvus vector database enabling AI assistants to search, query, and interact with vector data for semantic search and similarity matching applications. --- _Canonical page: https://mcpserver.ever.works/tags/vector-database_