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MariaDB AI Tools

Datasheet

01
Introduction

Enterprises are eager to adopt agentic AI to unlock the value in their data. But Large Language Models (LLMs) are prone to hallucination and lack context about your specific business, leading to inaccurate or irrelevant answers.

The solution is Retrieval-Augmented Generation (RAG), a technique that grounds AI in your data. While RAG solves the accuracy problem, deploying it has traditionally been a nightmare of complexity. Stitching together separate vector databases, retrievers, and AI frameworks introduces security risks, high costs, and a steep learning curve.

02
MariaDB AI RAG

MariaDB AI RAG consolidates the entire RAG pipeline into a single, robust platform, providing benefits that multi-tool solutions can’t match.

Radical Simplicity

Forget the headaches of managing multiple vendors and complex integrations. MariaDB AI RAG includes native vector search and simple, developer-friendly APIs, eliminating the need for separate tools like LangChain or LlamaIndex and removing the requirement for deep Agentic AI expertise.

Flexible Integration via REST API

Connect any application, in any language—no complex database drivers or proprietary libraries required. Our REST API provides a universal endpoint, freeing your developers to build with the stack they already know and trust.

Uncompromising Security

A security-first approach ensures your sensitive data never leaves your environment. Unlike complex pipelines that move data between services, our solution keeps your data securely within your own MariaDB database.

Lower Total Cost of Ownership (TCO)

Leverage your existing MariaDB deployment and expertise. By adding RAG capabilities to the same platform you already trust, you eliminate the cost and complexity of purchasing, integrating, and managing a separate vector database and middleware.

Enterprise-Grade Performance

Built on MariaDB’s robust and scalable foundation, our RAG solution is tuned for the low-latency performance that enterprise applications demand.

03
MariaDB AI Agents

Take your AI capabilities to the next level by integrating MariaDB AI RAG with the MariaDB Enterprise MCP Server. This powerful combination allows an AI Agent to not only retrieve accurate information but also to reason and act on it.

AI Agent alone

Smart reasoning but limited or stale knowledge

RAG alone

Accurate retrieval, but no ability to act or automate

AI Agent +
MariaDB AI RAG

An autonomous, accurate, and adaptive system that can answer questions and perform tasks

04
MariaDB MCP Server

Natively integrate vector search, LLMs and standard SQL operations through the Model Context Protocol (MCP) to build the next generation of intelligent applications.

MCP provides a standardized way for language models and other AI systems to interact with external tools and data sources. The model-agnostic MariaDB MCP Server implements this protocol, ensuring a consistent and reliable method for AI assistants and applications to request information and perform operations. This approach streamlines the development and deployment of AI-integrated systems by enabling seamless communication between AI models and various data sources.

MariaDB MCP Server is engineered to provide a robust MCP interface specifically for MariaDB. Its primary objective is to facilitate seamless interaction between AI models and MariaDB databases, supporting both standard relational data operations and the increasingly vital vector search capabilities required for modern AI applications. Designed with AI agents in mind, it simplifies data workflows and enhances the ability to integrate database interactions into intelligent systems.

The Engine Behind the Intelligence

Embeddings allow the server to understand the semantic meaning. The MariaDB MCP Server integrates a flexible embedding service to generate these vectors.

Broad provider support

Works out of the box with leading embedding providers, including OpenAI, Google Gemini, and open models from HuggingFace.

Flexible model selection

Configure a default embedding model for your instance or specify a model on the fly for any request, allowing you to balance cost, performance and quality.

Supercharge Your Workflow

Bridge the gap between development and data. Connecting the MariaDB MCP Server with AI-native IDEs like Cursor and Windsurf makes your database a native component of your coding environment.

This integration allows you to interact with MariaDB using natural language directly within your editor – whether to run a standard SQL query or perform a complex vector search. There’s no need to switch to a separate database client, which reduces friction and keeps you in a state of flow.

05
About MariaDB

MariaDB seeks to eliminate the constraints and complexity of proprietary databases, enabling organizations to reinvest in what matters most – rapidly developing innovative, customer-facing applications. Enterprises can depend on a single complete database for all their needs, that can be deployed in minutes for transactional, analytical and hybrid use cases. Trusted by organizations such as Deutsche Bank, DBS Bank, ServiceNow and Samsung – MariaDB delivers customer value without the financial burden of legacy database providers. For more information, please visit mariadb.com.