Elasticsearch

Integrates with Elasticsearch clusters to enable natural language searching of indices, mapping retrieval, and data discovery without requiring knowledge of Elasticsearch query syntax

This MCP server provides direct integration with Elasticsearch clusters, enabling AI assistants to search indices, retrieve mappings, and list available indices through natural language interactions. Built with FastMCP and the official Elasticsearch Python client, it offers three core tools: search_index for query string searches, list_indices for discovering available data sources, and get_index_mappings for understanding data structure. The implementation includes a demonstration client using LangChain and Ollama's DeepSeek model, with example penalty kick data from CSV files, making it valuable for organizations that need AI-powered access to their Elasticsearch data warehouses, log analysis systems, or search infrastructure without requiring users to learn Elasticsearch query syntax.