"For years, APIs have served as the backbone of data access, but they were never designed with AI in mind. They lack memory, context, and intent awareness-forcing developers to bolt on brittle glue code every time models change. Anthropic's introduction of MCP earlier this year marked a turning point, offering a standardized way to make APIs context-aware and AI-ready. But as Chivukula points out, adopting MCP isn't just about creating a one-off server."
"The comparison to cloud migration is apt. Just as lift-and-shift approaches left organizations with bloated costs, treating MCP as a quick wrapper on existing APIs won't cut it. Instead, enterprises need a sustainable framework that refactors APIs for AI interaction, enforces security, and manages change continuously. Chivukula highlights integration with GitHub's vast ecosystem-home to tens of millions of API repositories-as a critical lever to reach both developers and enterprises."
APIs were designed without AI in mind and lack memory, context, and intent awareness, requiring fragile glue code when models change. Anthropic introduced the Model Context Protocol (MCP) to standardize making APIs context-aware and AI-ready. Enterprises operate tens of thousands of APIs, many undocumented or outdated, so MCP adoption requires a lifecycle approach rather than a one-off server. Continuous MCP server platforms automate creation, updates, and security scanning at scale, refactor APIs for AI interaction, enforce security, and manage ongoing change. Integration with GitHub's repository ecosystem enables discovery and adoption. MCP adoption scales across billions of APIs and is presented as inevitable.
Read at DevOps.com
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