Unifying Scattered AI Assets with 'MCP stdio'

When AI assets such as prompts, skills, and personas are scattered across multiple tools and repositories, it becomes difficult to identify the latest version or maintain consistent quality. As a centralization method to solve this, Agent Sync and MCP stdio can be compared.

Agent Sync is a method of downloading files from a central repository to a local machine. It's easy to directly check and customize file contents, but it has the drawback of version mismatches occurring due to manual synchronization, as well as the burden of duplicate management.

MCP stdio, on the other hand, is a method that builds a server using the Model Context Protocol (MCP) and communicates via standard input/output (stdio).

• Advantages: The latest assets deployed centrally can be automatically applied to all IDE/CLI environments, and it offers excellent extensibility such as tool calls and external integrations.
• Disadvantages: It requires tools that support MCP, and it's difficult to directly edit asset contents locally.

Implementation proceeds in the order of central package configuration, package distribution, IDE MCP registration, and agent usage. By creating an MCP server in src/index.ts and registering a prompts handler, markdown-form rules or skills are connected so that agents can use them immediately.