The Promise Of MCP — And The Importance Of An Enterprise-Ready Server

While AI ambitions are high, trust in the technology is still in flux. Many companies can’t confidently let AI agents automate routine tasks, like resetting a password, approving an order, or running a transaction. Instead, they struggle with getting agents to accurately and securely perform their duties the same way, every time.

This is common in technology transformations of this magnitude. For example, new protocols and governance had to be developed before companies could harness the power of the Internet in their own operations. Similarly, before organizations can successfully deploy and get value from AI agents, they must set up guardrails that enable the systems to have broad, secure access across the organization’s IT environment.

Several recent protocols aim to deliver this orchestration, but Model Context Protocol, or MCP, is emerging as the top choice. More than just IT plumbing, MCP increasingly serves as a glue connecting AI agents to core enterprise systems to transform common, multi-step workflows, like order-to-cash or record-to-report. Released by Anthropic in late 2024, there are already thousands of open-source MCP servers to choose from — reflecting the important role MCPs play in enterprise AI adoption. But as businesses rush to quickly infuse the power of AI into their operations, they must be careful about the foundation they choose.

"At Workato, we hear every day that while MCP is exciting, enterprises still face challenges making MCP work securely, effectively, and reliably at scale," Adam Seligman, Chief Technology Officer at Workato, said in Axios.

Many of the available MCP servers require companies to build necessary components themselves. Key requirements, like security, identity and access controls, and governance are custom add-ons, not features. Often, engineers start from scratch to rebuild environments every time. This complicates the IT environment. The AI agent is stuck navigating hundreds of API calls, leading to unreliable answers and actions.

First of its kind, Workato Enterprise MCP is the foundation organizations need to make the promise of AI agents a reality. Integrated seamlessly into existing applications and processes, Workato Enterprise MCP delivers unified governance and security across the AI agent fleet, giving IT teams the control they need to scale use of the technology and maximize the benefits. Meanwhile, pre-built, fully-managed servers make it easy to instantly turn any system or application into an MCP server.

"MCP is quickly becoming the standard for how AI works with corporate applications. With Workato Enterprise MCP, organizations can instantly unlock business capabilities with AI in a secure way from day one," Laurent Farci, Chief Information Officer at .monks, said in the Axios sponsored article.

For example, in a recent article, Canva Head of IT Michael Denari noted that Workato empowers users to build specialized MCP servers that reflect the organization’s knowledge graph and governance controls. In 2025, the company expects the technology to help reduce person-hours by as much as 30,000, Denari said.

MCP adoption is only growing — and that’s a problem for organizations that don’t take the time now to standardize. Workato Enterprise MCP provides a path to production without requiring teams to reinvent infrastructure every time. The business can quickly put AI to work in the real-world. As a result, AI agents are focused on delivering on KPIs, not APIs.