Vector

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Vector is an MCP server designed to provide a unified collection management system for AI agents interacting with various vector database technologies. Inspired by the RAG implementation in Microsoft's Autogen V1, it abstracts away database-specific complexities, allowing agents to easily create, manage, and query collections for retrieval augmented generation (RAG) across supported databases like ChromaDB, PGVector, Couchbase, Qdrant, and MongoDB.

Características Principales

• AI agent capabilities for collection creation and document addition from files or URLs
• Facilitates Retrieval Augmented Generation (RAG) workflows
• Supports ChromaDB, PGVector, Couchbase, Qdrant, and MongoDB
• Collection deletion functionality
• Standardized collection management across diverse vector databases
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Casos de Uso

• Enabling AI agents to interact seamlessly with various vector databases
• Standardizing data and collection management across diverse vector database platforms
• Implementing Retrieval Augmented Generation (RAG) systems with multiple backend options