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

MCP server providing backend access to PostgreSQL, Storage (Supabase/S3), Iceberg data lake, and SQL seeds. It offers 32 tools for database queries, storage operations, seed management, and more.

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

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 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.

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.

Connects ElevenLabs voice agents to Supabase for real-time order lookups, enabling voice agents to retrieve order status, tracking, and delivery information through the lookup_order tool.

Provides tools for managing project knowledge graphs, enabling structured representation of projects, tasks, milestones, resources, and team members.

Read-only MySQL/MariaDB MCP server for running SELECT queries safely, with automatic read-only enforcement and query limits.

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.

A cross-project knowledge graph for MCP that maps features across mobile, backend, and admin codebases, giving AI agents full-stack context.

Enables AI agents to perform read-only static analysis of Node.js backend projects, detecting database query anti-patterns, async bottlenecks, connection pooling mistakes, and dependency hygiene issues while returning structured evidence-backed findings.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

A database MCP server providing 33 tools across PostgreSQL, MySQL, and SQLite, with connection groups, rollback, dump/restore, and schema auto-discovery via natural language.

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

A local, provider-neutral MCP server for repository-scoped issue handling. It provides a guarded interface to Linear, GitHub Issues, GitHub Projects v2, and Jira Cloud, with preview/apply safety and host-local configuration.

An extensible MCP server for database operations that supports PostgreSQL for managing schemas, tables, data, and user permissions. It features automatic migration recording for DDL changes and integrates with various AI-powered editors like Cursor, Zed, and Claude Code.

Enables AI clients to read structured project context and propose task changes that require explicit human approval, with scoped permissions, idempotency, and a full audit trail.

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.