RESEARCH · RESEARCH · #1121
Model Context Protocol and Eunomia Agent propose mediation layer to connect LLM agents with Data Spaces (arXiv:2609.30341v1)
The paper proposes an architectural mediation approach using the Model Context Protocol (MCP), implemented in the Eunomia Agent, to translate data space capabilities into schema-driven tools LLM agents can discover and invoke. A prototype demonstrates end-to-end interactions for catalog discovery, metadata retrieval, and data service invocation without modifying existing data space components, aiming to preserve governance and interoperability.
KEY POINTS
- The paper proposes an architectural mediation approach using the Model Context Protocol (MCP), implemented in the Eunomia Agent, to translate data space capabilities into schema-driven tools LLM agents can discover and invoke.
- A prototype demonstrates end-to-end interactions for catalog discovery, metadata retrieval, and data service invocation without modifying existing data space components, aiming to preserve governance and interoperability.
- This matters because it offers a standards-aligned way for AI agents to operate within governed data-sharing infrastructures while preserving policy constraints and architectural separation.
WHY IT MATTERS
This matters because it offers a standards-aligned way for AI agents to operate within governed data-sharing infrastructures while preserving policy constraints and architectural separation.