"Connecting a backend project to an Elasticsearch database" matching MCP servers:

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

Read/write Elasticsearch mcp server with many tools

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.

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.

A read-only MCP server for Elasticsearch 7.10 clusters, providing tools for cluster info, health, index listing, and Query DSL search with Google OAuth and Bearer token authentication.

An MCP server that enables AI assistants to directly interact with Elasticsearch for searching, aggregating, and retrieving documents from indices, supporting full-text search, semantic search, and various query modes.

Read-only MCP server that converts Elasticsearch logs into citable evidence for AI agents, offering deterministic log summarization and search tools.

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.

Provides specialized analytics tools for querying VSee's Elasticsearch stats-\* indices, including account/group metrics, visit trends, platform breakdowns, rating distributions, and subscription tier analysis.

An MCP server that enables interaction with Elasticsearch and OpenSearch clusters for searching documents and managing indices. It provides tools for cluster health monitoring, index configuration, and general API requests.

Enables AI agents to operate an isolated local Chromium browser through MCP, with semantic snapshots, ref-based actions, search, research, crawling, and CDP access.

Transforms Elasticsearch into an AI-powered observability engine for analyzing logs, APM traces, and system metrics through natural language.

Provides a natural language interface for querying and managing PostgreSQL, MySQL, MariaDB, MSSQL, and SQLite databases using the Model Context Protocol. Users can explore database schemas and visualize query results through an integrated web dashboard.

Enables AI assistants to interact with PostgreSQL and Supabase databases through natural language. Supports secure database operations including queries, migrations, and schema management with user-provided credentials.

Read-only Text-to-SQL MCP server for PostgreSQL and MySQL that lets users query databases using natural language, with robust multi-layer safety guarantees against writes.

A high-performance MCP server that connects tools like Cursor to Elasticsearch clusters using public-key authorization instead of API keys. It provides optimized tools for searching data, listing indices, and inspecting cluster mappings or shards with support for concurrent requests.