Connects Claude and other MCP clients to Elasticsearch data, allowing users to interact with their Elasticsearch indices through natural language conversations.
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.
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.
Enables AI agents to inspect and query Elasticsearch clusters through six read-only tools for listing indices, reading mappings, searching with Query DSL or ES|QL, checking shards, and monitoring cluster health.
Enables secure and efficient interaction with Elasticsearch clusters through the Model Context Protocol, providing tools for data management, search, and export.
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.
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.
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.
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.
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 natural language interaction with a corporate SQLite database, allowing users to set up tables, add records, and search data through plain English commands.
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.
Enables AI agents to operate an isolated local Chromium browser through MCP, with semantic snapshots, ref-based actions, search, research, crawling, and CDP access.
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/).
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.
Provides a local, evidence-first knowledge base over source snapshots and summaries stored in SQLite, with bounded search and exact readback while preserving provenance.
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.
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.