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This research explores how integrating RAG, MCP, and LLMs can create secure and explainable cognitive systems within the .NET framework.

April 10, 2026Open Access

Cognitive Systems Architecture: Integration of RAG, MCP and LLMs in the .NET Ecosystem

Key Points

This research explores how integrating RAG, MCP, and LLMs can create secure and explainable cognitive systems within the .NET framework.
Examined the architecture of cognitive systems using RAG, MCP, and LLMs.
Analyzed governance and monitoring practices for these systems.
Discussed technical challenges related to integration and future trends.
Identified key benefits of integration, including enhanced security and explainability.
Outlined future trends for improving trustworthiness and audibility in AI systems.

Abstract

The integration of RAG, MCP, and LLMs into the .NET ecosystem enables robust, explainable, and secure cognitive systems, applicable in domains such as legal, biomedical, and corporate support. The article details fundamentals, architecture, and practices for orchestration, governance, and monitoring of these systems, as well as discussing technical challenges and future trends for trustworthy, auditable, and mission-critical AI.

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Authors

Nagib Sabbag Filho

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Universidade Paulista

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Cognitive Systems Architecture: Integration of RAG, MCP and LLMs in the .NET Ecosystem

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Abstract

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Connected Papers

Discussion

Authors

Actions

Institutions

References and Citations

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Connected Papers

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