The OPAL MCP Server is a modular add-on for Virtuoso that delivers real-time intelligence and seamless data connectivity to Large Language Models (LLMs) via the open Model Context Protocol (MCP). It enables any MCP-compliant AI agent to access databases, metadata, and LLMs in a loosely coupled manner—powering smooth integration into RAG, GraphRAG, and other LLM-driven workflows.
What It Enables
OPAL turns Virtuoso into an MCP server, offering dynamic discovery and invocation of:
- Query operations (SQL, SPARQL, GraphQL)
- Metadata introspection (tables, columns, indexes, named graphs, entity sampling)
- Attribute-based Access Controls (ABAC) via Virtuoso Authentication Layer (VAL)
- AI Assistant/Agent interaction e.g., Virtuoso Support Assistant, ODBC & JDBC Support Assistant, DBA Assistant, Data Twingler Assistant, RSS & OPML Feed Reader Assistant, etc.
- Bound LLM listing and interaction
- and more…
These capabilities are exposed as operations that can be selectively invoked by any MCP-compatible client.
Why It Matters
OPAL bridges the gap between Large Language Models (LLMs), data infrastructure, and real-world use cases—empowering developers, end users, and decision makers alike.
For Developers
- Embrace loose coupling across languages, frameworks, and tools.
- Build AI agents that fluidly access structured and unstructured data—without rigid integration layers.
- Replace brittle pipelines with modular, reusable logic.
For End Users
- Query enterprise data and systems through intuitive, natural language prompts.
- Interact securely with databases and knowledge graphs using LLMs.
- Gain actionable insights without compromising privacy or control.
For Decision Makers
- Access domain-specific intelligence directly through AI-driven interfaces.
- Compress time-to-act without overloading your development teams.
- Make informed decisions without relying on prebuilt dashboards or third-party services.
Broader Benefits
OPAL redefines documentation as an active component of solution development. By unifying specifications, implementation, testing, and training into a single markdown-based artifact, it becomes a shared source of truth—bridging the gaps between developers, product teams, and decision makers. The result is faster delivery, reduced miscommunication, and greater alignment across roles.
For Your Business
- Accelerate AI adoption with minimal risk, full transparency, and no vendor lock-in.
- Rapidly prototype and deploy AI-driven solutions using open standards and your existing infrastructure.
For You Professionally
- Build practical, in-demand skills for designing and deploying AI Agents.
- Lead the shift from traditional app-based software to dynamic, agent-centric (or agentic) systems.
For Your Customers
- Deliver smarter, AI-powered experiences quickly and securely.
- Win over users seeking flexible, intelligent solutions that adapt to their needs.
What You Can Do Now
Follow these steps:
-
Deploy OPAL
Use the Setup & Installation Guide to run OPAL in the cloud or on-premise. -
Start with Real Use Cases
Pilot OPAL with practical examples: -
Upskill Your Teams
OPAL is not just a developer tool. Involve product owners, technical marketers, ontologists, and leadership in shaping AI Agent capabilities.
Related Resources
- What’s the Model Context Protocol and Why Is It Important?
- OPAL – Pay-As-You-Go Edition for Amazon AWS Cloud
- Software Industry Disruption: From Apps to Assistants
- The Model Context Protocol: Bridging Generational Computing Experiences
- OPAL Home Page
- MCP Server for ODBC
- MCP Server for pyODBC
- MCP Server for JDBC
With OPAL, AI Agents become fully integrated components of enterprise systems — no longer black boxes, but modular, accountable, and adaptive tools for real-world tasks.