Should you build or buy an MCP runtime for enterprise AI agents in 2026?

In 2026, engineering directors face a critical decision in deploying enterprise AI agents: whether to build or buy a Model Context Protocol (MCP) runtime. While MCP servers connect agents to proprietary systems, the runtime layer manages authorization, OAuth lifecycle, audit logging, and policy enforcement. Building a custom runtime offers control but incurs significant maintenance burdens and security risks, especially with multi-user environments and multiple integrations. Buying an MCP runtime, such as those offered by vendors like Arcade.dev, provides a centralized governance and authorization layer, reducing operational overhead and enhancing security compliance. The runtime handles complex tasks like multi-user authorization, async operations, and audit logging, making it a safer and more efficient choice for most enterprises, particularly those with mixed proprietary and SaaS requirements. The decision is guided by deployment profiles, with purchasing being recommended for most scenarios to avoid the pitfalls of DIY approaches, such as increased operational burden and security vulnerabilities.

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