Elasticsearch is a distributed, free and open search and analytics engine for all types of data, including textual, numerical, geospatial, structured, and unstructured.
Why this server?
Provides access to Elasticsearch indices, allowing users to list indices, inspect field mappings, and execute search queries using full Query DSL capabilities with automatic highlighting.
Why this server?
Connects to the NixOS Elasticsearch API to query package information and system options with field-specific search boosts, multiple channel support, and error handling.
Why this server?
Provides Elasticsearch interaction allowing users to search documents, analyze indices, and manage clusters through natural language queries
Why this server?
Provides product specification search capabilities through Elasticsearch indexes, allowing for detailed product comparisons based on technical specifications
Why this server?
Connects to Elasticsearch clusters allowing interaction with indices through natural language, including listing indices, retrieving mappings, performing searches, managing index templates, bulk operations, reindexing data, and monitoring cluster health.
Why this server?
Enables interaction with Elasticsearch 7.x instances, supporting basic operations like ping and info, as well as complete search functionality including aggregation queries, highlighting, sorting, and other advanced search features.
Why this server?
Uses Elasticsearch as the backend for the knowledge graph, providing distributed, scalable storage for entities and relations with advanced search capabilities
Why this server?
Provides integration with ElasticSearch, enabling AI agents to query and search through data via automatically generated APIs.
Why this server?
Provides access to Elasticsearch data by exposing it as relational SQL models through the CData JDBC Driver.
Why this server?
Allows querying Elasticsearch data through SQL interfaces.
Why this server?
Enables SQL querying of Elasticsearch indices and documents
Why this server?
Enables querying Elasticsearch indices and documents through SQL-like syntax.
Why this server?
Listed as a supported data source for integration with the MCP server, allowing access to Elasticsearch data.
Why this server?
Enables SQL-based querying of Elasticsearch indices and documents.
Why this server?
Provides SQL-based querying of Elasticsearch search and analytics engine.
Why this server?
Listed as a supported data source for querying Elasticsearch indices and data.
Why this server?
Enables SQL-based querying of Elasticsearch indices and documents.
Why this server?
Enables access to Elasticsearch data through SQL queries.
Why this server?
Provides tools for querying and retrieving data from Elasticsearch indices.
Why this server?
Provides querying capabilities for Elasticsearch data through SQL models.
Why this server?
Listed as a supported data source for integration through the CData JDBC driver.
Why this server?
Allows querying Elasticsearch data through SQL interfaces, making search engine data accessible via natural language.
Why this server?
Listed as a supported data source in the compatibility table, enabling access to Elasticsearch data.
Why this server?
Planned for Q4 2025 to provide search-optimized AI interactions with Elasticsearch, enabling context-aware queries and operations.
Why this server?
Enables read-only access to Elasticsearch data, allowing SQL-like queries against Elasticsearch indices and documents.
Why this server?
Enables SQL-based querying of Elasticsearch indices and documents.
Why this server?
Listed as a supported data source for integration, allowing access to Elasticsearch data through the MCP server.
Why this server?
Enables querying of Elasticsearch indices and documents through relational SQL models.
Why this server?
Listed as a supported data source for integration through the CData JDBC Driver
Why this server?
Provides SQL-based access to Elasticsearch indexes and documents, allowing relational queries against search engine data.
Why this server?
Provides search capabilities for court decisions using Elasticsearch query syntax, allowing for complex queries against the entscheidsuche.ch legal database
Why this server?
Retrieves security alerts from Elasticsearch indices containing Wazuh data, transforming them into standardized MCP messages.
Why this server?
Enables vector search capabilities for AI queries, allowing efficient similarity searches and semantic retrieval of data stored in Elasticsearch indices.
Why this server?
Provides tools for interacting with Elasticsearch clusters, including health checks, statistics retrieval, index management, document searching with AI-generated queryDSL, and shard allocation monitoring.
Why this server?
The MCP server provides semantic search functionality through Elasticsearch, enabling users to search through Search Labs blog posts that have been indexed using Elastic Open Crawler.
Why this server?
Enables management of Elasticsearch clusters, allowing for creating indices, indexing documents, listing available indices, and executing search queries using Elasticsearch query DSL.