dev-plan-mcp

rhys117/dev-plan-mcp

3.2

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The MCP Plan Server is a sophisticated tool designed to manage development plans with AI agent orchestration, providing structured workflow management for development tasks.

Tools
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Resources
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Prompts
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MCP Plan Server

An MCP (Model Context Protocol) server for managing development plans with AI agent orchestration. This server provides structured workflow management for development tasks with built-in AI agent integration.

Quick Start

1. Build the Server

cd mcp-plan-server
npm install
npm run build

2. Initialize Your Project

Run the initialization in your project directory:

# From your project root
npm run init
# Or if using the built CLI:
node /path/to/mcp-plan-server/dist/cli.js init

This creates:

  • .llms/prompts/ - Customizable orchestrator prompts
  • .claude/agents/ - Autonomous sub-agent definitions
  • .claude/commands/ - Claude Code slash commands
  • .llms/workflows.yml - Workflow configuration

3. Start the MCP Server

# Development mode with auto-reload
npm run dev

# Production mode
npm start

4. Configure Claude Code MCP

Add to your Claude Code MCP configuration:

{
  "mcpServers": {
    "plan-server": {
      "command": "node",
      "args": ["/absolute/path/to/mcp-plan-server/dist/index.js"]
    }
  }
}

Usage

Slash Commands (Recommended)

# Create and execute plans
/plan "Implement user authentication" medium
/execute-plan
/execute-full-plan

# Use orchestrator prompts
/prompt scope-analyst
/prompt implementer --planFile=".llms/.dev-plan-main.yaml"

MCP Tools

// Create main plan
create_plan({
  taskDescription: "Implement user authentication",
  workflow: "medium",
  priority: "high"
})

// Update plan progress
update_plan({
  planFile: ".llms/.dev-plan-main.yaml",
  stage: "implementation",
  sectionData: { changes: ["Added auth middleware"] }
})

// Create subtask
create_subtask_plan({
  subtaskDescription: "Add JWT token validation",
  workflow: "small",
  priority: "high"
})

// List all plans
list_plans({ includeSubtasks: true })

// Get next steps
get_workflow_next_steps({ planFile: ".llms/.dev-plan-main.yaml" })

Sub-Agents

// Spawn autonomous execution
Task({
  subagent_type: "general-purpose",
  description: "Execute implementation phase",
  prompt: "Load plan-mcp-implementation agent and execute it for .llms/.dev-plan-main.yaml"
})

Architecture

The MCP Plan Server operates on a dual-layer approach:

Orchestrator Layer (.llms/prompts/):

  • Manual guidance prompts for Claude Code
  • Interactive workflow management
  • Customizable phase-specific instructions

Agent Layer (.claude/agents/):

  • Autonomous execution agents
  • Complete workflow implementations
  • Spawn via Task tool for hands-off operation

Workflow Stages

StagePurposeOutput
scope_analysisClassify complexity, decompose tasksfindings{}
context_gatheringExplore codebase, find patternsfindings{}
solution_designCreate technical architectureartifacts{}, checklist[]
implementationWrite actual codechanges[]
validationTest and verify requirementsresults{}
documentationCreate user documentationfiles[]
knowledge_captureExtract learnings and insightslearnings{}

Customization

  • Prompts: Edit .llms/prompts/*.md for personalized guidance
  • Workflows: Modify .llms/workflows.yml for custom stages
  • Sub-Agents: Customize .claude/agents/*.md for autonomous behavior

Workflow Types

  • micro: Single file, trivial changes (scope_analysis → implementation → validation)
  • small: 2-3 files, straightforward (+ context_gathering)
  • medium: Multiple files, moderate complexity (+ solution_design + documentation)
  • large: Many files, significant changes (+ knowledge_capture)
  • epic: Major feature requiring decomposition (all stages)

File Structure

Your Project/
├── .llms/
│   ├── .dev-plan-main.yaml          # Main plan
│   ├── workflows.yml                # Workflow configuration
│   ├── prompts/                     # Orchestrator prompts
│   └── .dev-plan-main/
│       └── subtasks/
│           ├── .dev-plan-auth.yaml  # Subtask plans
│           └── .dev-plan-api.yaml
└── .claude/
    ├── agents/                      # AI agents
    │   ├── plan-mcp-scope-analysis.md
    │   ├── plan-mcp-implementation.md
    │   └── ...
    └── commands/                    # Slash commands
        ├── plan.md
        ├── execute-plan.md
        └── ...

Available Tools

Core Tools

  • create_plan - Create a new main development plan
  • create_subtask_plan - Create an independent subtask plan
  • update_plan - Update a development plan stage
  • read_plan - Read a development plan file
  • list_plans - List all development plans
  • promote_subtask - Promote a subtask to independent plan
  • get_workflow_next_steps - Get next steps for a plan
  • create_workflows_file - Create or update workflows.yml
  • list_workflows - List all available workflows

Custom Workflows

Customize workflows in .llms/workflows.yml:

workflows:
  # Built-in workflows
  micro:
    description: "Single file, trivial changes"
    steps: [scope_analysis, implementation, validation]
  
  # Custom workflows
  api_development:
    description: "API-focused development"
    steps: [api_design, schema_validation, implementation, testing, documentation]

default:
  description: "Minimal workflow for quick tasks"
  steps: [scope_analysis, implementation]

Features

  • 🎯 Workflow-driven: Plans automatically configure stages based on task complexity
  • 🔧 Customizable: Define custom workflows and stages for your specific needs
  • 📝 Comprehensive tracking: Each stage has specialized data structures for relevant information
  • 🔗 Hierarchical: Main plans can have independent subtask plans with their own workflows
  • ✅ Validation: Built-in validation ensures proper stage progression and data integrity
  • 🛠️ MCP Integration: Full Model Context Protocol support for AI agent integration
  • 📊 Progress tracking: Visual progress through workflow stages with completion status
  • 🚀 Extensible: TypeScript-based with comprehensive type definitions and error handling