Search Meilisearch indexes using vector embeddings to find semantically similar content, supporting hybrid text-vector searches and customizable filtering.
Conduct vector-based searches in a Meilisearch index using JSON arrays or text queries, with options for filtering, hybrid searches, and result customization for precise data retrieval.
A secure vector-based memory server that provides persistent semantic memory for AI assistants using sqlite-vec and sentence-transformers. It enables semantic search and organization of coding experiences, solutions, and knowledge with features like auto-cleanup and deduplication.
Provides local vector-based semantic memory storage for AI assistants to persist context and decisions across sessions using local embeddings and LanceDB. It enables private semantic search and session handoff capabilities to maintain long-term project context.
Model Context Protocol (MCP) server implementation for semantic search and memory management using TxtAI. This server provides a robust API for storing, retrieving, and managing text-based memories with semantic search capabilities. You can use Claude and Cline AI Also