Pinecone
Manages and queries a Pinecone vector database for similarity search, semantic search, and RAG applications.
Acerca de
mcp-pinecone acts as a dedicated server for the Pinecone vector database, providing a robust interface for storing, managing, and searching high-dimensional embeddings. It supports a wide array of AI-driven applications by offering features like comprehensive index management, efficient vector operations (upsert, query, fetch), similarity search with various metrics, and powerful metadata filtering. The tool is designed to facilitate use cases such as Retrieval Augmented Generation (RAG), semantic search, and recommendation systems, ensuring data isolation through namespaces and supporting both serverless and pod-based Pinecone index types.
Características Principales
- Namespaces for data isolation and multi-tenancy
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- Vector Operations (upsert, query, fetch, update, delete)
- Metadata Filtering for hybrid search
- Index Management (create, list, describe, delete)
- Similarity Search (cosine, euclidean, dot product metrics)
Casos de Uso
- Recommendation Systems (similar item recommendations)
- Semantic Search (find similar documents or products)
- RAG (Retrieval Augmented Generation for LLM context)
