Skip to main content
  1. Projects/

mcp-multiverse

·3 mins

Universal MCP Server Synchronization Manager #

mcp-multiverse is a universal synchronization manager for Model Context Protocol (MCP) servers across multiple AI platforms including Claude Code, Gemini CLI, Cline, and Roo Code.

Core Functionality #

Multi-Platform Sync #

  • Claude Code: Syncs MCP configurations across Claude Code installations
  • Gemini CLI: Manages Gemini-specific MCP servers
  • Cline: Synchronizes Cline MCP configurations
  • Roo Code: Handles Roo Code MCP server setups

Key Features #

Configuration Backup #

  • Automatic Backups: Creates timestamped backups before any changes
  • Safety First: Never modifies configs without backup
  • Recovery System: Restore from any backup if needed

Smart Synchronization #

  • Platform Detection: Automatically detects available platforms
  • Selective Sync: Choose which platforms to sync
  • Conflict Resolution: Handles configuration conflicts intelligently

Zero Dependencies #

  • Pure Python: Uses only Python standard library
  • No External Packages: No requirements.txt or dependencies
  • Lightweight: Minimal resource footprint
  • Portable: Works anywhere Python is available

Technical Implementation #

Pure Python Standard Library #

# No external dependencies required
import json
import os
import shutil
import datetime
from pathlib import Path

Configuration Management #

  • JSON Parsing: Native JSON handling for config files
  • Path Resolution: Cross-platform path handling
  • Backup Creation: Automatic timestamped backup directories
  • Diff Detection: Identifies configuration changes

Platform Integration #

  • Claude Code: Locates and manages Claude-specific MCP configs
  • Gemini CLI: Handles Gemini MCP server configurations
  • Cline: Syncs Cline MCP settings
  • Roo Code: Manages Roo Code MCP setups

Usage Scenarios #

Development Workflows #

  • Multi-IDE Support: Develop across Claude Code and other platforms
  • Config Consistency: Ensure same MCP servers everywhere
  • Team Collaboration: Share MCP configurations across team

Platform Migration #

  • Easy Switching: Move between Claude Code and alternatives
  • Data Preservation: Backup before migration
  • Quick Setup: Restore configs on new installations

Configuration Management #

  • Version Control: Track configuration changes over time
  • Experimentation: Try new MCP servers safely with backups
  • Rollback: Restore previous configs if needed

Architecture Highlights #

Safety-First Design #

  • Backup Everything: No operation without backup
  • Read-Only Detection: Prevents accidental config corruption
  • Rollback Support: Restore any previous state

Cross-Platform Compatibility #

  • Path Handling: Works on Windows, macOS, Linux
  • Platform Detection: Identifies available MCP platforms
  • Adaptive Logic: Platform-specific handling when needed

Minimal Footprint #

  • Single File: Entire tool in one Python file
  • Standard Library Only: No dependencies to install
  • Fast Execution: Quick startup and operation

Benefits #

For Developers #

  • Time Savings: No manual config copying
  • Safety: Automatic backups prevent loss
  • Consistency: Same MCP servers across platforms

For Teams #

  • Standardization: Shared MCP configurations
  • Onboarding: New members get consistent setups
  • Collaboration: Unified toolchain

For Experimentation #

  • Safe Testing: Try new MCP servers without risk
  • Easy Rollback: Restore configs instantly
  • A/B Comparison: Compare different configurations

Technical Notes #

No External Dependencies #

  • Uses only Python built-in modules
  • No pip install required
  • Works in restricted environments

Cross-Platform Path Handling #

  • Proper path separators for each OS
  • Home directory resolution
  • Hidden directory support

Backup Strategy #

  • Timestamped backup directories
  • Multiple backup retention
  • Easy restoration process

Impact #

mcp-multiverse demonstrates practical Python programming and MCP (Model Context Protocol) expertise while solving a real problem in the AI developer ecosystem.