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

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

A Docker-based local RAG backend that provides advanced document search capabilities using vector, graph, and full-text retrieval via the Model Context Protocol. It supports over 28 file formats and tracks evolving relationships between concepts using a Neo4j-backed graphiti implementation.

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.

MCP server for Microsoft SQL Server that lets LLMs explore schema and execute read-only SELECT queries, with optional stored procedure execution when explicitly enabled.

Local workspace memory for Claude Desktop. Indexes documents into a vector store with hybrid search, cross-session memory, auto-learn, and knowledge graph.

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.

A Model Context Protocol server that enables LLMs to interact with databases (currently MongoDB) through natural language, supporting operations like querying, inserting, deleting documents, and running aggregation pipelines.

A Model Context Protocol server that enables LLMs like Claude to interact with SQLite and SQL Server databases, allowing for schema inspection and SQL query execution.

An MCP server that provides deterministic math computation (numeric, symbolic, unit, matrix) and hybrid retrieval over study notes/textbooks with citations, helping Claude become a reliable study partner.

Enables Claude to query and manage databases (SQLite, SQL Server, PostgreSQL, MySQL) through natural language, supporting read/write operations and schema management.

This read-only MCP Server allows you to connect to Elasticsearch data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

Provides universal database operations for AI assistants through MCP, supporting 40+ databases including PostgreSQL, MySQL, MongoDB, Redis, and SQLite with built-in introspection tools for schema exploration.

Enables coding agents to retrieve compact, cited repository maps through MCP tools such as search, symbol inspection, flow investigation, and deep context loading.

Enables users to interact with an e-commerce shopping assistant using natural language to search products, check prices and ratings, compare items, and get personalized recommendations.

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.

Enables GitHub Copilot and other LLMs to execute read-only SQL queries against Oracle databases with secure connection pooling and schema introspection capabilities.

A Python MCP server that gives LLMs persistent, searchable access to project context — documentation, architecture decisions, and session notes.

Enables LLM agents to search and retrieve a hybrid knowledge base of manuals, videos, PDFs, DOCX files and images through tools for hybrid BM25-plus-vector search with facet and tag filters, full document retrieval, semantically similar document lookup, and timestamped video transcript segments. It ships with an in-memory backend for instant local use and an identical Elasticsearch backend for production deployment over stdio or authenticated HTTP.

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.

Connects to Elasticsearch databases using the Model Context Protocol, allowing users to query and interact with their Elasticsearch indices through natural language conversations.

Hardware-accelerated codebase mapping that indexes Git repositories into Postgres/pgvector and serves code search, relationships, and static analysis results via a stdio MCP server.

It enables users to interact with a codebase through hybrid retrieval, code graph navigation, impact analysis, and context preparation for AI coding agents.

A tool that creates MCP (Model Context Protocol) servers from OpenAPI/Swagger specifications, enabling AI assistants to interact with your APIs.

Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.

Enables hybrid retrieval-augmented generation with semantic and keyword search over documents, supporting multiple formats and providing MCP integration for Claude Desktop.

Exposes Elasticsearch semantic search capabilities as MCP tools, enabling ELSER, kNN, and hybrid search with automatic index setup.

Enables agents to search and retrieve past workspace conversations, dialogue transcripts, and markdown artifacts through local BM25 retrieval, providing cross-conversation architectural recall with low-latency, offline operation.

Routes coding agents to the most relevant project documentation (decisions, intent, constraints) with provenance and freshness, providing tools for task routing, knowledge search, and document context.

Enables Claude to connect to and interact with SQLite, SQL Server, PostgreSQL, and MySQL databases through natural language. Supports executing queries, managing tables, exporting data, and storing business insights with authentication options including AWS IAM.

Provides project-aware context for coding agents by selecting relevant AGENTS.md, docs, module paths, and decision records based on task, reducing redundant context loading via MCP stdio.