Vector
Manages standardized collection operations across multiple vector database technologies for AI agents.
About
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.
Key Features
- 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
- 0 GitHub stars
Use Cases
- 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
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