"Querying Elasticsearch (ES)" matching MCP servers:

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

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

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/).

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.

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.

An MCP server that indexes PDF documentation and text into Elasticsearch for semantic search and retrieval. It enables users to query knowledge bases, ingest new files, and dynamically update content through MCP-compatible clients like Claude Desktop and Cursor.

Dual-memory MCP system with PostgreSQL 17 + pgvector + NVIDIA NIM embeddings. 11 tools: search, save, profile, health, auto-repair, stats, tune, dedup, checkpoint, maintenance. Sparse Selective Caching (SSC) with 4-phase progressive retrieval. Bilingual EN/ES.

Complete knowledge management for AI assistants with Elasticsearch search and document management.

Connects to Elasticsearch clusters through the Model Context Protocol, enabling natural language querying and management of Elasticsearch data. Provides tools to search indices, list available indices, and retrieve index mappings.

An MCP server for Chinese financial reports, providing 44 tools to resolve companies, list/retrieve filings, extract report sections, run AI-based indicator extraction, search via Elasticsearch, and browse a 21,698-rule industry rules dashboard.

Provides an MCP protocol interface for interacting with Elasticsearch 7.x databases, supporting comprehensive search functionality including aggregations, highlighting, and sorting.

Enables searching imported AI conversations locally across different providers from an MCP client, with read-only access to the archive.

Enables building and querying a Markdown-based knowledge graph with hybrid vector, keyword, and graph retrieval, community detection, and evidence-grounded answers through isolated workspaces.

MCP-Server from your Database optimized for LLMs and AI-Agents. Supports PostgreSQL, MySQL, ClickHouse, Snowflake, MSSQL, BigQuery, Oracle Database, SQLite, ElasticSearch, DuckDB

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

Persistent, searchable archive and memory for Claude and ChatGPT. Native macOS MCP server, install from the App Store, no setup. Private, local and open source.

An Elasticsearch-based AI memory system optimized for Chinese that enables persistent knowledge storage and complex entity relationship management via the Model Context Protocol. It features advanced semantic search using the IK analyzer and supports multi-zone memory isolation for specialized knowledge graphs.

Enables querying a modular RAG knowledge base via MCP, with hybrid retrieval, reranking, and document summary tools.

A Model Control Protocol server that integrates with Claude Desktop to enable simultaneous querying and cross-checking of responses from multiple LLM providers including OpenAI, Anthropic, Perplexity AI, and Google Gemini.

Enables querying of live organizational data (student records, outcomes, certifications, finances, donations, communications) via Claude using structured database queries and semantic search.

A Python MCP server that enables semantic search through Search Labs blog posts indexed in Elasticsearch, allowing Claude to intelligently retrieve relevant information from the blog content.

A template for creating MCP servers in Node.js/TypeScript with a modular architecture. It simplifies adding new tools and includes an example Elasticsearch search tool.

Connects LLMs to Elasticsearch with a Semantic-to-Lexical layer that translates technical field names into business knowledge, enabling autonomous querying without hardcoded domain logic.

Enables LLM-powered search with Elasticsearch, including query planning, expansion, and intelligent filtering for e-commerce.

Enables querying Brazilian PCDT clinical protocols from Conitec and generating concise, context-specific treatment summaries using a local LLM, with verified literal citations and links to official PDFs.

A local, offline memory server for AI agents that stores and retrieves memories without LLM calls, enabling persistent cross-session memory with bi-temporal querying and auditable records.

Local MCP server for semantic code search using Tree-sitter AST parsing, local embeddings, and hybrid search; enables indexing and querying codebases entirely offline.

Index docs websites and local folders, then let Claude, Cursor, or any MCP client answer from the current docs, with a link to every section it used.

Enables indexing local documents (PDF, Markdown, text, code) into a knowledge base and querying them via semantic search using local embeddings, all running privately on your machine.

It converts documents to Markdown or docling JSON for AI agents. That covers PDFs with layout analysis, table structure and OCR, plus DOCX, PPTX, XLSX, HTML, EPUB, e-mail, images and audio. It serves MarkItDown's "convert_to_markdown" tool under the same name and contract, along with "convert" and "list_input_formats".