Open-source alternatives to Mcp Database Server

Connect ClickHouse to your AI assistants.

Reference MCP servers that are no longer maintained

An official Qdrant Model Context Protocol (MCP) server implementation

StarRocks MCP (Model Context Protocol) Server

MCP server for interacting with SingleStore Management API and services

Model Context Protocol Servers in Quarkus

A Model Context Protocol (MCP) server for GreptimeDB

Model Context Protocol server for Aiven

Axiom Model Context Protocol Server

Unofficial Codex skill and MCP server for operating Docker-based local-ydb deployments.

1. 入门示例: tablestore-java-mcp-server 2. 基于 MCP 架构实现知识库答疑系统: tablestore-java-mcp-server-rag - 实现一个目前最常见的一类 AI 应用即答疑系统，支持基于私有知识库的问答，会对知识库构建和 RAG 做一些优化。

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Query MCP enables end-to-end management of Supabase via chat interface: read & write query executions, management API support, automatic migration versioning, access to logs and much more.

Bytebase is a database DevSecOps platform and management console designed to orchestrate schema migrations, deployments, and security audits across multiple database engines. It serves as a SQL GitOps tool that synchronizes database states with configurations stored in Git repositories to manage infrastructure as code. The platform distinguishes itself through a multi-database management console that provides a single interface for relational and NoSQL databases. It includes a security layer for role-based access control, database activity auditing, and column-level data masking to protect se

mcp server for tidb

This repository has been merged into Canner/WrenAI under the core/ directory

Universal MCP-Server for your Databases optimized for LLMs and AI-Agents.

Chartbrew is a self-hosted business intelligence platform and data visualization engine designed to transform raw data from SQL databases and external API endpoints into interactive charts and dashboards. It serves as a tool for building analytics dashboards that monitor business metrics and KPIs through a privately hosted environment. The platform distinguishes itself with an embedded analytics workflow, allowing users to generate secure, time-limited shared links and iframes to display private charts on external websites. It also provides programmatic chart generation via API and integrates

Model Context Protocol (MCP) for interacting with dicom servers (PACS etc.)

This project is an MCP browser automation server that connects large language models to headless cloud browsers. It functions as an autonomous web workflow engine and an LLM web agent interface, enabling the translation of natural language instructions into browser actions and structured data retrieval. The system distinguishes itself through a managed headless browser cloud API that supports concurrent Chromium sessions with integrated stealth modes, CAPTCHA solving, and proxy traffic routing. It utilizes self-healing element selection to maintain automation resilience when page structures c