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MCP Worktree Voting Server

by Doctacon

MCP Git Worktree Workflows

An MCP (Model Context Protocol) server that implements automated parallel development using git worktrees.

🚀 Key Features

  • Voting Workflow: Intelligently ranks and selects the highest-quality implementation
  • Ad Hoc Workflow: Quick single-worktree creation for simple tasks
  • Orchestration Workflow: Break complex tasks into subtasks with coordinated execution
  • Clean Workflow: Automatic cleanup of unsuccessful variants

Installation

  1. Install dependencies:
uv add fastmcp # or pip install fastmcp
  1. Add the server to Claude Code:
# For project-specific use claude mcp add worktree-workflows python /path/to/mcp-servers/worktree_workflows.py # For global use across all projects claude mcp add --scope user worktree-workflows python /path/to/mcp-servers/worktree_workflows.py

Option B: Manual Configuration

Add to your MCP configuration file:

{ "mcpServers": { "worktree-workflows": { "command": "python", "args": ["/path/to/mcp-servers/worktree_workflows.py"] } } }
  1. Restart Claude Code or use /mcp command to reconnect

🔄 Workflow Options

1. Voting Pattern (Multiple Implementations)

create_voting_worktrees( task="Rewrite the README.md with better examples", num_variants=5, target_repo="lombardi" # Optional: specify repository )

2. Ad Hoc Single Worktree

create_adhoc_worktree( task="Fix the login bug in auth.js", target_repo="my-app" # Optional )

3. Orchestrated Subtasks

create_orchestrated_worktrees( task="Implement user authentication system", subtasks=[ "Create database models for users and sessions", "Build authentication API endpoints", "Implement JWT token generation and validation", "Create login/logout UI components", "Add authentication middleware and route protection" ], target_repo="my-app" # Optional )

📊 Evaluation Metrics

The system automatically evaluates implementations using:

  • Code Changes (30 points): Has meaningful modifications
  • Test Success (50 points): Tests pass successfully
  • File Impact (up to 20 points): Number of files modified
  • Quality Heuristics: Additional scoring based on implementation patterns

🛠️ Available Tools

Core Voting Workflow

  • create_voting_worktrees: Creates worktrees and starts automated execution
  • list_sessions: Monitor all active sessions and their progress
  • evaluate_implementations: Get detailed ranking and evaluation of all variants
  • auto_select_best: Automatically choose and finalize the best implementation
  • finalize_best: Manually select a specific implementation
  • cleanup_session: Force cleanup of sessions

Additional Workflows

  • create_adhoc_worktree: Single worktree for quick tasks
  • create_orchestrated_worktrees: Multiple worktrees for coordinated subtasks

Utility Functions

  • get_worktree_info: Inspect specific worktree details
  • mark_implementation_complete: Manually mark implementations as done

💡 Example Use Cases

Voting Pattern

Perfect for:

  • Architecture Exploration: Try different design patterns simultaneously
  • Library Comparison: Implement with various frameworks/libraries
  • Algorithm Optimization: Test multiple approaches to performance problems
  • UI/UX Variants: Create different interface implementations

Ad Hoc Tasks

Great for:

  • Bug Fixes: Quick isolation and resolution
  • Small Features: Rapid implementation without overhead
  • Experiments: Try ideas without affecting main branch

Orchestrated Development

Ideal for:

  • Large Features: Break down and parallelize development
  • System Refactoring: Coordinate multiple related changes
  • API Development: Build endpoints, models, and tests in parallel

🎯 Quick Start Examples

Example 1: Voting Pattern

# 1. Start automated voting session create_voting_worktrees( task="Add Redis caching to the user service with error handling", num_variants=3 ) # 2. Check progress (Claude is working automatically) list_sessions() # Returns: "2/3 complete, 3/3 executed" # 3. View results and rankings evaluate_implementations(session_id="xyz789") # Shows ranked implementations with scores # 4. Auto-select winner and merge auto_select_best(session_id="xyz789", merge_to_main=true) # Merges best implementation, cleans up others

Example 2: Quick Fix

# Create single worktree for a bug fix create_adhoc_worktree( task="Fix null pointer exception in user profile component" ) # Claude starts immediately in new Terminal window

Example 3: Feature Development

# Break down complex feature into subtasks create_orchestrated_worktrees( task="Add real-time notifications", subtasks=[ "Set up WebSocket server infrastructure", "Create notification database schema and models", "Build notification API endpoints", "Implement frontend notification component", "Add notification preferences to user settings" ] ) # 5 Terminal windows open, each with Claude working on a subtask

⚡ Performance Notes

  • Concurrent Execution: All Claude instances run in parallel
  • Automatic Cleanup: Failed/low-quality implementations are removed
  • Resource Efficient: Only keeps the winning implementation
  • Fast Evaluation: Uses git diff stats and automated test detection
  • Smart Naming: Worktrees include task description for easy identification

🔧 Advanced Features

Worktree Naming

  • Branches and directories now include task descriptions
  • Format: {session-id}-{task-slug}-{variant}
  • Example: abc123-fix-login-bug-var1

Origin/Main Support

  • Ad hoc worktrees always branch from origin/main
  • Ensures clean starting point for isolated tasks
  • Automatically fetches latest changes

Terminal Integration

  • Automatically spawns Terminal windows (macOS)
  • Each worktree gets its own Claude session
  • No manual terminal management required

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