An emerging standard that connects AI agents with data sources and tools has garnered substantial attention and recently introduced new features, including support from cloud-native infrastructure companies. AI agents, which are autonomous software components supported by large language models (LLMs) capable of taking autonomous action and leveraging external tools to complete tasks, have seen a surge in interest due to the expansion of agentic AI over the past year.
Among the various frameworks for orchestrating and integrating AI agents that have emerged, the Model Context Protocol (MCP) stands out as a prominent player in the industry. Introduced by AI vendor Anthropic in November, MCP has quickly gained traction and sparked partnerships with major generative AI players, as well as integration with hundreds of IT tool vendors. Microsoft and OpenAI recently unveiled new integrations with MCP, indicating a growing trend towards adopting this protocol in the AI ecosystem.
The addition of support for MCP in tools like OpenAI’s Agents SDK and Microsoft’s Playwright web testing and automation tool set has captured the attention of industry professionals. One such individual, Mahender Singh, a site reliability engineer at a financial services company, expressed interest in how MCP could simplify the consumption of tools like Playwright for developers within his organization.
Further emphasizing MCP’s relevance, AWS launched a set of MCP servers for its code assistants, while cloud-native player Kubiya unveiled an agentic AI platform at KubeCon + CloudNativeCon Europe that integrates with MCP. Kubiya’s CEO, Amit Govrin, highlighted the importance of embracing MCP as a standard protocol to enhance user experiences within their platform.
As MCP continues to evolve, industry analysts have noted areas for improvement, such as enhancing user authentication and supporting service discovery for remote access. Additionally, a more formal multivendor governance structure is seen as a crucial step to ensure the protocol’s widespread adoption and interoperability.
Despite initial concerns regarding the proprietary nature of Anthropic’s Claude AI model and desktop client, cloud-native infrastructure vendors have actively joined the MCP community to address any existing gaps. Companies like MinIO, Cloudflare, and Solo.io have introduced MCP servers and extensions to support their products, contributing to the overall growth of the MCP ecosystem.
Meanwhile, other projects like Agntcy, led by Cisco, LangChain, and Galileo, have introduced their own agent connect protocol with a focus on enabling AI agents to interact with each other. While still in its early stages, Agntcy presents a different approach compared to MCP, emphasizing the importance of standardizing agent interactions within the AI landscape.
Overall, the growing momentum behind MCP and its expanding ecosystem signal a shift towards a more interconnected and collaborative approach to AI development and deployment. As the protocol continues to evolve and address user feedback, it is poised to play a pivotal role in shaping the future of AI integration and interoperability across various platforms and tools.