Bridging LLM Agents and Data Spaces: An Architectural Mediation Approach using the Model Context Protocol
Bridging the gap between sovereign data infrastructures and autonomous AI agents using standardized protocols.
Data Spaces enable sovereign and governed data sharing across organizational boundaries, but their integration with AI agents remains challenging due to mismatches between probabilistic language model interactions and policy-driven data infrastructures. This article presents an a...
ArXiv CS.AI
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The integration of Model Context Protocol with Data Spaces creates a standardized bridge that allows AI agents to interact with sovereign data while respecting complex organizational governance. This architecture overcomes the current fragmentation in the AI ecosystem by providing a reliable framework for secure, policy-compliant data retrieval.
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