"A server for searching for 'dbhup'" matching MCP servers:

MCP server that connects AI assistants to Redash, enabling listing of assets, read-only query execution, dashboard inspection, and alert management through the Redash API.

A safety-gated Python MCP server for Metabase that lets MCP clients and agents inspect Metabase, run governed queries, and create or maintain dashboards, cards/questions, collections, snippets, permissions, and other Metabase assets through the Metabase REST API.

Enables exploring Microsoft Fabric / Power BI workspaces and semantic models, and executing ad-hoc DAX queries.

Enables AI applications to run SQL queries and retrieve results from Oracle Database.

This MCP server provides secure access to databases for AI agents, enforcing authentication, authorization, human approval, logging, and notifications to prevent dangerous actions.

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.

Connect to your TTRPG campaign's repository and database. Instead of retrieving prose, its 48 tools (20 read, 28 write) return typed state: 14 entity schemas (NPCs, factions, locations, sessions, lore), relationship and knowledge-graph queries, wiki blocks, and a narrative-state bundle of open threads and canon facts.

Give your AI agent the entire China A-share market: 55 datasets of prices, financials, capital flows, corporate events and futures/options, stored locally and queryable with read-only SQL. Built point-in-time with delisted stocks kept, so backtests don't lie — no account, no API key.

Enables MCP clients such as GitHub Copilot, Codex, Claude... to explore a SQL Server 2017+ database read-only: databases, schemas, tables, views, procedures, functions, indexes and dependency graphs, plus filtered, grouped, sampled and paginated queries capped by row limits.

Enables secure access to Oracle databases with fine-grained access control, supporting multiple databases simultaneously with configurable access modes (readonly/readwrite/full) and table-level permissions for safe query execution and data management.

Provides access to MySQL databases with fine-grained access control, supporting multiple databases simultaneously with configurable access modes (readonly, readwrite, full) and table-level permissions using whitelists, blacklists, wildcards, and regex patterns.

A TypeScript-based server to interact with ArangoDB using the Model Context Protocol, enabling database operations and integration with tools like Claude and VSCode extensions for streamlined data management.

Provides a scalable knowledge graph implementation for Model Context Protocol using Elasticsearch, enabling AI models to store and query information with advanced search capabilities, memory-like behavior, and multi-zone architecture.

MCP server that allows Claude AI to interact directly with MySQL databases, enabling query execution and table information retrieval through natural language.

MCP Server for Apache Pinot

Enables integration with OpenMetadata by wrapping its REST API for standardized interaction through the Model Context Protocol.

Java based Model Context Procotol (MCP) Server for JDBC

A FastMCP integration server that provides access to Apache Gravitino metadata management APIs, allowing users to manage catalog/schema/table metadata, tags, and user-role information through a structured interface.

Enables AI applications to securely access and manage PostgreSQL data in Azure via MCP tools for querying, updating, and schema operations.

Enables users to ask natural-language questions about live 1C:Enterprise data and receive answers from read-only OData sources, covering sales, inventory, items, and counterparties; supports direct connections or an SSH tunnel for IP-allowlisted installations.

Enables AI agents to query and modify RDF data, list named graphs, and access pre-built SPARQL templates on a Fuseki server, with optional HTTP Basic authentication.

A Machine Control Protocol (MCP) server that enables storing and retrieving information from a Qdrant vector database with semantic search capabilities.

A Model Context Protocol server that connects AI agents to Apache Jena, enabling them to execute SPARQL queries and updates against RDF data stored in Jena Fuseki.

A Model Context Protocol server that enables LLMs to interact directly with MongoDB databases, allowing users to query collections, inspect schemas, and manage data through natural language.

Enables AI clients to securely interact with Oracle databases using natural-language prompts, translating requests into structured queries and returning results for AI-powered data access.

Enables AI clients to interact with PostgreSQL databases through natural language, translating requests into structured queries and returning results via a secure self-hosted server.

A Model Context Protocol (MCP) Server that allows AI models to securely interact with data hosted in Azure Database for PostgreSQL. It enables natural language querying, schema exploration, and data management through MCP clients like Claude Desktop and Visual Studio Code.

Enables document CRUD and bounded read-only aggregation over MongoDB collections through controlled actions with secure connection and write-safety handling.

A server that enables document searching using Vertex AI with Gemini grounding, improving search results by grounding responses in private data stored in Vertex AI Datastore.

Provides a semantic memory layer that integrates LLMs with OpenSearch, enabling storage and retrieval of memories within the OpenSearch engine.