MCP server for OpenSearch that enables AI assistants to interact with OpenSearch clusters through a standardized interface for search, index management, and cluster operations.
An MCP server that indexes PDF documentation and text into Elasticsearch for semantic search and retrieval. It enables users to query knowledge bases, ingest new files, and dynamically update content through MCP-compatible clients like Claude Desktop and Cursor.
An MCP server that enables AI agents to interact with OpenSearch, including searching indices, managing documents, creating and deleting indexes, checking cluster health, and monitoring statistics.
A Model Context Protocol server that enables LLMs to interact with Elasticsearch clusters, allowing them to manage indices and execute search queries using natural language.
An MCP server that provides semantic search capabilities by integrating with an OpenSearch-based search service. It enables users to perform complex document searches across multiple indices with support for advanced filtering and robust error handling.
An MCP server that provides semantic search over a document corpus, enabling AI clients to retrieve and cite relevant chunks from indexed documents via RAG pipelines.