International Journal of Computer
Trends and Technology

Research Article | Open Access | Download PDF

Volume 73 | Issue 8 | Year 2025 | Article Id. IJCTT-V73I8P1021 | DOI : https://doi.org/10.14445/22312803/IJCTT-V73I8P102

Integrating Generative AI and Model Context Protocol (MCP) with Applied Machine Learning for Advanced Agentic AI Systems


Nilesh Bhandarwar

Received Revised Accepted Published
08 Jun 2025 12 Jul 2025 30 Jul 2025 18 Aug 2025

Citation :

Nilesh Bhandarwar, "Integrating Generative AI and Model Context Protocol (MCP) with Applied Machine Learning for Advanced Agentic AI Systems," International Journal of Computer Trends and Technology (IJCTT), vol. 73, no. 8, pp. 7-14, 2025. Crossref, https://doi.org/10.14445/22312803/IJCTT-V73I8P102

Abstract

Generative AI, Model Context Protocol (MCP), and Applied Machine Learning (ML) combine to provide a compelling means to power advanced agentic AI systems that are able to make decisions autonomously and to learn how to do better over time. This paper explores how these technologies can be integrated to improve the performance, flexibility, and intelligence of agentic AI systems. With generative AI, businesses can generate new data and, therefore, new insights, but MCP is what ensures these AI models are contextually aware and can function in different environments or conditions. Applied ML adds a new level of realism to model training and real-world deployment, proving that AI can learn, adapt, and make intelligent decisions on the fly. This paper presents the synergy of these building blocks and proposes a unified framework that combines their strength to develop intelligent context-aware agents that work independently in dynamic, complex environments. This integrated framework is widely applicable in domains like healthcare, finance, and robotics, where adapting decision-making abilities is important.

Keywords

Generative AI, Model Context Protocol, Applied Machine Learning, Agentic AI, Autonomous Decision-Making, Adaptive Systems.

References

[1] Deepak Bhaskar Acharya, Karthigeyan Kuppan, and B. Divya, “Agentic AI: Autonomous Intelligence for Complex Goals–A Comprehensive Survey,” IEEE Access, vol. 13, pp. 18912-18936, 2025.
[CrossRef] [Google Scholar[Publisher Link]
[2] Laurie Hughes et al., “AI Agents and Agentic Systems: A Multi-expert Analysis,” Journal of Computer Information Systems, vol. 65, no. 4, pp. 489-517, 2025.
[CrossRef] [Google Scholar[Publisher Link]
[3] Ranjan Sapkota, Konstantinos I. Roumeliotis, and Manoj Karkee, “AI agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenges,” arXiv preprint arXiv:2505.10468, 2025.
[CrossRef] [Google Scholar[Publisher Link]
[4] Venus Garg, “Designing the Mind: How Agentic Frameworks Are Shaping the Future of AI Behavior,” Journal of Computer Science and Technology Studies, vol. 7, no. 5, pp. 182-193, 2025.
[CrossRef] [Google Scholar[Publisher Link]
[5] Soodeh Hosseini, and Hossein Seilani, “The Role of Agentic AI in Shaping a Smart Future: A Systematic Review,” Array, vol. 26, 2025.
[CrossRef] [Google Scholar[Publisher Link]
[6] San Murugesan, “The Rise of Agentic AI: Implications, Concerns, and The Path Forward,” IEEE Intelligent Systems, vol. 40, no. 2, pp. 8-14, 2025.
[CrossRef] [Google Scholar[Publisher Link]
[7]  Nalan Karunanayake, “Next-generation Agentic AI for Transforming Healthcare,” Informatics and Health, vol. 2, no. 2, pp. 73-83, 2025.
[CrossRef] [Google Scholar[Publisher Link]
[8] Erik Miehling et al., “Agentic AI Needs a Systems Theory,” arXiv preprint arXiv:2503.00237, 2025.
[CrossRef] [Google Scholar[Publisher Link]
[9] Ashis Kumar Pati, “Agentic AI: A Comprehensive Survey of Technologies, Applications, and Societal Implications,” IEEE Access, 2025.
[CrossRef] [Google Scholar[Publisher Link]
[10] Yonadav Shavit et al., “Practices for Governing Agentic AI Systems,” Research Paper, OpenAI, 2023.
[Google Scholar[Publisher Link]
[11] Alan Chan et al., “Harms from Increasingly Agentic Algorithmic Systems,” Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, pp. 651-666, 2023.
[CrossRef] [Google Scholar[Publisher Link]
[12] Daniel Ogbu, “Agentic AI in Computer Vision Domain-recent Advances and Prospects,” International Journal of Research Publication and Reviews, vol. 4, no. 12, pp. 5102-5120, 2023.
[Google Scholar]
[13] Abhishek Dodda, “AI Governance and Security in Fintech: Ensuring Trust in Generative and Agentic AI Systems.,” American Advanced Journal for Emerging Disciplinaries (AAJED), vol. 1, no. 1, 2023.
[Google Scholar[Publisher Link]
[14] Shengran Hu, Cong Lu, and Jeff Clune, “Automated Design of Agentic Systems,” arXiv preprint arXiv:2408.08435, 2024.
[CrossRef] [Google Scholar[Publisher Link]
[15] Ai Zuo, “The Rise of Autonomous AI Agents: Automating Complex Tasks,” International Journal of Artificial Intelligence for Science (IJAI4S), vol. 1, no. 2, 2025.
[CrossRef] [Google Scholar[Publisher Link]
[16] Uwe Borghoff, Paolo Bottoni, and Remo Pareschi, “Human-artificial Interaction in the Age of Agentic AI: A System-Theoretical Approach,” Frontiers in Human Dynamics, vol. 7, 2025.
[CrossRef] [Google Scholar[Publisher Link]
[17] Kapal Dev et al., “Advanced Architectures Integrated with Agentic AI for Next-generation Wireless Networks,” arXiv preprint arXiv:2502.01089, 2025.
[CrossRef] [Google Scholar[Publisher Link]
[18] Fouad Bousetouane, “Agentic Systems: A Guide to Transforming Industries with Vertical AI Agents,” arXiv preprint arXiv:2501.00881, 2025.
[CrossRef] [Google Scholar[Publisher Link]
[19] Mourad Gridach et al., “Agentic AI for Scientific Discovery: A Survey of Progress, Challenges, and Future Directions,” arXiv preprint arXiv:2503.08979, 2025.
[CrossRef] [Google Scholar[Publisher Link]
[20] Varun Bodepudi et al., “Agentic AI and Reinforcement Learning: Towards more Autonomous and Adaptive AI Systems,” Journal for Educators, Teachers and Trainers, vol. 11, no. 1, 2020.
[CrossRef] [Google Scholar]
[21] Jiangbo Yu, “From Autonomy to Agency: Agentic Vehicles for Human-Centered Mobility Systems,” arXiv preprint arXiv:2507.04996, 2025.
[CrossRef] [Google Scholar[Publisher Link]
[22] Chhavi Chawla et al., “Agentic AI: The Building Blocks of Sophisticated AI Business Applications,” Journal of AI, Robotics & Workplace Automation, vol. 3, no. 3, pp. 196-210, 2024.
[CrossRef] [Google Scholar[Publisher Link]
[23] Mohammad Reza Boskabadi et al., “Industrial Agentic AI and Generative Modeling in Complex Systems,” Current Opinion in Chemical Engineering, vol. 48, 2025.
[CrossRef] [Google Scholar[Publisher Link]
[24] Balagopal Ramdurai, “Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) Systems, and Convolutional Neural Networks (CNNs) in Application Systems,” International Journal of Marketing and Technology, vol. 15, no. 1, 2025.
[Google Scholar]
[25] Balagopal Ramdurai, and Prasanna Adhithya, “The Impact, Advancements and Applications of Generative AI,” SSRG International Journal of Computer Science and Engineering, vol. 10, no. 6, pp. 1-8, 2023.
[CrossRef] [Google Scholar[Publisher Link]