"How to write a query in Elasticsearch" matching MCP servers:

A minimal MCP server with get_weather and create_ticket tools, used for testing MCP servers across protocol, unit, eval, transport, and auth layers.

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

Enables AI assistants to search, analyze, and interact with Elasticsearch through natural language.

Read/write Elasticsearch mcp server with many tools

An AI recipe recommendation server based on the MCP protocol, providing functions such as recipe query, classification filtering, intelligent dietary planning, and daily menu recommendation.

Connects agents to Elasticsearch data using the Model Context Protocol, allowing natural language interaction with Elasticsearch indices through MCP Clients like Claude Desktop and Cursor.

Enables secure and efficient interaction with Elasticsearch clusters through the Model Context Protocol, providing tools for data management, search, and export.

Enables read-only interaction with Elasticsearch, supporting listing indices, retrieving mappings, and executing search/aggregation queries via MCP.

Enables Claude Desktop to connect directly to Elasticsearch clusters for intelligent log analysis through natural language queries. Users can ask questions about their logs in plain English and get actionable insights without writing complex Elasticsearch queries.

Enables AI agents to read and optionally write to PostgreSQL databases through a multi-project setup with schema inspection, query execution, and performance analysis tools.

A local MCP server for secure database querying from Claude Code, with Apple Keychain credential storage, permission-based access control, and audit logging.

MCP server for querying and analyzing TensorBoard event files, enabling AI agents to extract scalar data, statistics, and correlations without a running TensorBoard server.

Facilitates interaction with Elasticsearch clusters by allowing users to perform index operations, document searches, and cluster management via a Model Context Protocol server and natural language commands.

Connects Claude and other MCP clients to Elasticsearch data, allowing users to interact with their Elasticsearch indices through natural language conversations.

This is an elasticsearch mcp server developed based on sprint ai.

Enables AI agents to create document timestamps on a VerusID, writing directly to the Verus blockchain via a local or remote daemon.

Enables comprehensive interaction with Elasticsearch APIs through natural language queries, specifically optimized for security analysis, threat detection, incident investigation, and compliance monitoring with advanced machine learning capabilities for anomaly detection.

Enables writing to CellarTracker by moving bottles between bins or locations and logging consumption, with planning, execution, and verification of outcomes using an authenticated session.

Enables AI assistants to make real in-place edits to Google Drive files—preserving file IDs, revision history, comments, and sharing—while also supporting appends, targeted find-and-replace, reads, searches, and file creation.

Provides persistent, intelligent memory using Elasticsearch with hierarchical categorization and semantic search for LLM contexts.