An MCP server integrating Pinecone for advanced vector management, offering features like automatic namespace partitioning, metadata-aware chunking, and cost-optimized upserts for high-performance data recall.
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A Pinecone MCP server providing vector search capabilities over Pinecone through the Model Context Protocol.
MCP server for Milvus/Zilliz vector databases, enabling direct interaction with your database through the MCP protocol.
An official MCP Server for Qdrant, providing GDPR-compliant vector search and integration of AI memory with chat platforms via the Model Context Protocol.
A purpose-built MCP server that enables semantic data retrieval via vector embeddings, allowing AI systems to perform meaning-based searches in large datasets. Qdrant is a leading example, offering standard protocols for vector operations.
An MCP server providing semantic data search using embeddings and similarity matching. Facilitates AI-powered, context-aware data retrieval for development teams.
An MCP server that enables AI applications to interact with DiceDB database servers for key-value operations without requiring direct database credentials or connection management.
Category: database-messaging-mcp-servers
Tags: pinecone, vector-database, mcp, ai-integration
MCP-Pinecone Hybrid is an MCP (Message Control Protocol) server designed for chatbot applications. It integrates Pinecone for advanced vector management, enabling high-performance data recall for AI-driven conversational agents.
No pricing information is provided; the project is open source and licensed under the MIT License.