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

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

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.

Enables SQL database interaction with true server-side result paging, runtime-managed connection profiles, and SSH-bridged access for PostgreSQL.

Intent-based project documentation server that automatically maps natural language queries to the right sources (plans, todos, roadmap, docs) and provides comprehensive task management with dependency tracking, backlog promotion, and archival workflows.

A stateful MCP server that remembers what your AI agent has already seen.

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.

A self-contained Claude Code plugin that profiles a project by running a fixed DAG to emit agent-facing context pages, a human/developer guide, and a queryable vectorstore.

Analyzes Python project structure by exploring directory trees, extracting outlines from Python and Markdown files, and inspecting OpenAPI specifications.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

MCP server for structured Laravel project planning. Scans projects, creates tickets, and exports as JSON.

Read-only MySQL MCP server that lets AI agents list tables, describe schemas, and run SELECT/SHOW/EXPLAIN queries with a row cap, bound to a single database for safety.

A Middleware/Control Plane server that allows AI code agents to securely execute queries against various databases (PostgreSQL, MySQL, MongoDB, Oracle) without directly exposing credentials.

A Python framework that exposes developer tools through MCP, REST API, and CLI from a single shared registry, enabling AI assistants, HTTP clients, and terminal users to access the same tools.

Enables any MCP-compatible agent to query, diagnose, map, and operate Elasticsearch or OpenSearch clusters via REST, with read-only defaults and layered safety controls.

Provides SQLite database analytics operations through MCP, enabling AI assistants to connect, query, explore schema, and export data from SQLite databases.

Indexes Unreal Engine project C++ source, config files, dependencies, gameplay tags, replication, asset references, and log categories into a SQLite database and exposes tools for AI assistants to query structural and config info.

Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.

A comprehensive tutorial project that teaches Model Context Protocol (MCP) development from beginner to advanced levels, covering both server-side and client-side development.

Loads CSV files into a temporary SQLite database and provides comprehensive data analysis tools via MCP, enabling AI assistants to query, analyze, and export data using natural language.

A lightweight MCP bridge that lets Claude Code delegate heavy tasks to the Antigravity CLI - saving context window and tokens for what matters.