Solr
Createdallenday
Enables AI assistants to perform powerful search queries against Solr indexes by combining keyword and vector search capabilities.
About
Solr is a Python package that integrates Apache Solr indexes with AI assistants via the Model Context Protocol (MCP). It empowers AI models like Claude to execute advanced search queries, leveraging both keyword precision and vector-based semantic understanding. This allows for hybrid search capabilities, combining traditional keyword search with the nuanced understanding of vector embeddings, all within a unified Solr collection. The package includes tools for generating embeddings using Ollama and nomic-embed-text, and provides a Docker-based setup for easy deployment.
Key Features
- Supports hybrid search combining keyword and vector search
- Provides Docker integration for easy setup
- Implements the Model Context Protocol for AI assistant integration
- Utilizes unified collections to store both document content and vector embeddings
- Generates vector embeddings for documents using Ollama
Use Cases
- Creating AI-driven knowledge bases with combined keyword and vector search
- Enhancing AI assistant's search capabilities against large document repositories
- Implementing semantic search within Solr-powered applications