navigating the Emerging Landscape of Multi-Party Compute (MCP) Servers: Build, Buy, or a Phased Approach?
The rise of AI agents is fueling demand for Multi-Party Compute (MCP) servers, and a growing ecosystem is stepping up to meet that need. But with options ranging from in-house progress to off-the-shelf solutions, how do organizations determine the best path forward? Let’s break down the strategies and explore a surprisingly effective hybrid approach.
who’s Supporting the MCP Revolution?
Many organizations are already embracing MCPs, and adoption is accelerating. Salesforce, for example, showcases MCP servers within its AgentExchange, functioning as an “app store” for AI agent connectivity. This allows companies to quickly integrate necessary services without extensive development, saving valuable time and resources.
The Core Debate: Build vs. Buy
Traditionally,the decision boiled down to a build-versus-buy scenario.Marcus McGehee, founder of The AI Consulting Lab, highlights key considerations. building in-house is ideal when compliance, performance optimization, or data sovereignty are paramount. Conversely, a managed MCP solution excels when flexibility, scalability, and predictable costs are prioritized over complete customization.
However, a third, increasingly popular option is emerging.
The Phased Approach: Best of Both Worlds
Instead of choosing one path exclusively, many are adopting a phased strategy: buy to learn, build to differentiate. This approach allows organizations to quickly establish baseline capabilities using commercial MCP servers. This initial phase focuses on understanding real-world integration patterns and validating business value.
Jesse Flores, founder and CEO of SuperWebPros, champions this method. He advises starting with readily available solutions to gain practical experience before selectively investing in custom development where a true competitive advantage can be realized.
validating the Strategy: Time-to-Learning
flores emphasizes a critical metric: time-to-validated-learning. If you can demonstrate tangible business value with a purchased solution within 90 days, you’ve built a strong case for a more targeted build strategy, backed by actual usage data. This data-driven approach minimizes risk and maximizes ROI.
A Gradual Internalization of Expertise
This isn’t just a theoretical concept. Industry experts like Jain corroborate the trend, noting that many organizations begin by purchasing MCP solutions and gradually internalize development as their AI capabilities mature.This allows for a controlled transition, leveraging external expertise while building internal competency.
Making the Right Choice for Your Organization
The MCP landscape is dynamic. A phased approach offers a pragmatic solution, allowing organizations to navigate the evolving technology while strategically building competitive advantages. By starting with commercial solutions, you can accelerate learning, validate use cases, and ultimately make informed decisions about where to invest in custom development.
