Making AI Agents Work in Enterprises
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Summary
The Model Context Protocol (MCP) is an open standard designed to unify the way AI models connect with external data sources, services, and tools. Originally introduced by Anthropic, MCP has rapidly gained support from industry leaders.
Here, we explore MCP’s value proposition, technical architecture, enterprise benefits, implementation best practices, and real-world use cases, culminating in recommendations for organizations seeking to modernize their AI strategy.
What’s Inside the White Paper
- The need for standardization in connecting LLMs with external sources and enterprise tools
- A detailed look at Model Context Protocol (MCP) and how it reimagines AI orchestration for enterprises
- How MCP enables modular, multi-agent systems that work seamlessly across data, APIs, and AI applications
- Strategies for integrating pre-trained models, enterprise logic, and compliance workflows in one platform
- Real-world applications and enterprise use cases across BFSI, compliance, automation, and customer intelligence
MCP solves a key challenge: the standardization of connecting LLMs to external sources. But what does it mean for enterprises? Could there be a multi-agent orchestration platform that does everything on one platform, i.e., connect to external sources, pre-trained AI applications, and enterprise data? Download the whitepaper to learn more.
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