MCP Server JSON Sync

The MCP Server JSON Sync tool tackles a common pain point for developers who configure Model Context Protocol (MCP) servers in Visual Studio Code and then need those same settings to be available across multiple AI assistants. Rather than manually editing each assistant’s configuration file, this repository provides a lightweight, automated workflow that pulls the section from VS Code’s and pushes it to the target applications. The result is a single source of truth that keeps every assistant in sync, reducing configuration drift and the risk of mismatched server definitions.

At its core, the tool is a set of three small Python scripts—one for each supported assistant (Cline, RooCode, and Windsurf). Each script follows the same pattern: read the current MCP configuration from VS Code, merge it into the target’s config file (creating the file if necessary), and write the updated JSON back. This approach preserves any existing settings in the target files while ensuring that new or modified MCP servers are propagated immediately. The scripts are intentionally minimal to keep the dependency surface small and make troubleshooting straightforward.

Automation is achieved through systemd timers that run hourly by default. When you install a sync target, the installer places the script in your directory and creates corresponding user‑level systemd service and timer units. The timers trigger the script once per hour, guaranteeing that any changes you make in VS Code are reflected across all assistants without manual intervention. For developers who need an instant update, a helper script offers an interactive menu to sync on demand.

Real‑world use cases include teams that rely on different IDE extensions or cloud‑based assistants but want a unified MCP configuration. For example, a developer might configure multiple language model servers in VS Code for local testing and then need those same servers available in a remote AI assistant used by the QA team. The sync tool eliminates repetitive copy‑paste tasks and ensures that server URLs, authentication tokens, and other parameters remain consistent. It also supports scenarios where an assistant is added or removed; the installer can be rerun for a new target, and the existing timer infrastructure will pick up the change automatically.

Beyond basic synchronization, the MCP Server JSON Sync offers several standout advantages:

• Single source of truth: All MCP server definitions live in VS Code, making the configuration visible and editable in one place.
• Zero‑touch updates: Once set up, the system runs silently in the background, keeping all assistants current without user action.
• Cross‑platform compatibility: The scripts rely only on Python and standard JSON handling, so they work on any Linux distribution that supports systemd.
• Extensibility: Adding support for a new assistant is as simple as duplicating the existing folder structure and adjusting file paths—no complex reconfiguration required.

In summary, MCP Server JSON Sync streamlines the developer experience by automating the propagation of MCP server settings across multiple AI assistants. It reduces configuration errors, saves time, and ensures that every tool in the developer’s stack works with the same server definitions—exactly what modern AI workflows demand.