Enables Retrieval Augmented Generation (RAG) systems by providing a Python server that leverages OpenAI's vector store capabilities using the Model Context Protocol (MCP).
Sponsored
This Python-based server utilizes the Model Context Protocol (MCP) and OpenAI's vector store capabilities to facilitate Retrieval Augmented Generation (RAG) systems. It allows users to create vector databases from various file types within a specified directory and query these databases to retrieve relevant information. The server offers tools for creating and querying vector databases, integrating with Claude apps, and testing via MCP Inspector.
Key Features
01Offers tools for creating and querying vector databases.
02Provides testing capabilities via MCP Inspector.
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04Supports querying vector databases for relevant information.
05Creates vector databases from files (text, PDF, DOCX, Markdown).
06Integrates with Claude apps.
Use Cases
01Creating chatbots that can answer questions based on local files.
02Integrating local document search into AI applications.
03Building RAG systems using local knowledge bases.