MCP Product Development Lifecycle (PDL) Server

Overview

The MCP PDL Server is a Model Context Protocol server that enables AI agents to track, manage, and collaborate on product development projects through their complete lifecycle. It provides structured phase management, sprint tracking, and role-based agent profiles to facilitate intelligent project coordination.

Core Concepts

Product Development Lifecycle (PDL) Phases

The server manages 7 distinct phases of product development:

1. Discovery & Ideation - Problem validation and idea generation
2. Definition & Scoping - Requirements and planning
3. Design & Prototyping - UX/UI design and testing
4. Development & Implementation - Code construction
5. Testing & Quality Assurance - Quality verification
6. Launch & Deployment - Release management
7. Post-Launch: Growth & Iteration - Performance monitoring and improvement

Multi-Project Support

• Projects are identified by unique project names (keys)
• Each project maintains independent phase states and sprint data
• Concurrent project tracking with isolated data contexts

Role-Based Agent Profiles

Each role has specific responsibilities and phase involvement:

• Product Manager - Vision, strategy, and coordination
• Product Designer - User experience and interface design
• Engineering Manager - Technical leadership and resource management
• Software Engineers - Implementation and technical execution (must know to follow best coding practices)
• QA Engineers - Quality assurance and testing
• Marketing Manager - Go-to-market strategy and positioning
• Sales & Support - Customer feedback and frontline insights

Agent Format

---
name: {name}
description: {when to use this agent}
tools: {tools}
model: model [sonnet | opus]
color: {color}
---

## Primary Responsibility
{description}

## Phase Leadership
{map of primary driver | key support | consultative}

## Key Responsibilitis by Phase

## Collaboration Matrix

## Success Metrics

## DOs
{important considerations to adhere to}

## DONTs
{anti-patterns we want to avoid}

MCP Server Specification

Server Name

mcp_pdl

Core Functions

1. get_phase

Retrieves the current phase information for a project.

Parameters:

• project_name (string, required): Unique project identifier
• include_sprints (boolean, optional): Include sprint details in response

Returns:

{
  "project_name": "string",
  "current_phase": {
    "phase_number": "integer (1-7)",
    "phase_name": "string",
    "status": "not_started | in_progress | completed | blocked",
    "start_date": "ISO 8601 datetime",
    "end_date": "ISO 8601 datetime or null",
    "primary_driver": "role name",
    "completion_percentage": "integer (0-100)"
  },
  "sprints": [] // if include_sprints is true
}

2. update_phase

Updates phase status and details for a project.

Parameters:

• project_name (string, required): Unique project identifier
• phase_number (integer, optional): Phase to update (1-7), defaults to current
• status (string, optional): "not_started" | "in_progress" | "completed" | "blocked"
• completion_percentage (integer, optional): 0-100
• notes (string, optional): Update notes or blockers
• transition_to_next (boolean, optional): Auto-transition to next phase if current is completed

Returns:

{
  "success": "boolean",
  "project_name": "string",
  "updated_phase": {
    "phase_number": "integer",
    "phase_name": "string",
    "status": "string",
    "completion_percentage": "integer"
  },
  "message": "string"
}

3. track_progress

Records and retrieves progress updates for sprints within phases.

Parameters:

• project_name (string, required): Unique project identifier
• action (string, required): "create_sprint" | "update_sprint" | "get_sprints" | "get_timeline"
• sprint_data (object, conditional): Required for create/update actions
  • sprint_name (string): Sprint identifier
  • phase_number (integer): Associated phase (1-7)
  • tasks (array): Task list with status
  • velocity (integer): Story points or task completion rate
  • blockers (array): Current impediments

Returns:

{
  "success": "boolean",
  "project_name": "string",
  "action": "string",
  "data": {} // Varies by action type
}

4. initialize_project

Creates a new project with PDL phase structure.

Parameters:

• project_name (string, required): Unique project identifier
• description (string, optional): Project description
• team_composition (object, optional): Role assignments
• start_phase (integer, optional): Starting phase (default: 1)

Returns:

{
  "success": "boolean",
  "project_name": "string",
  "phases_initialized": "array of phase objects",
  "message": "string"
}

Data Storage Structure

Project Schema

{
  "project_name": "string (unique key)",
  "description": "string",
  "created_at": "ISO 8601 datetime",
  "updated_at": "ISO 8601 datetime",
  "team_composition": {
    "product_manager": "string or array",
    "product_designer": "string or array",
    "engineering_manager": "string",
    "engineers": "array",
    "qa_engineers": "array",
    "marketing_manager": "string",
    "sales_support": "array"
  },
  "phases": {
    "1": { /* phase object */ },
    "2": { /* phase object */ },
    // ... through 7
  },
  "sprints": [
    { /* sprint objects */ }
  ],
  "activity_log": [
    { /* timestamped events */ }
  ]
}

Phase Schema

{
  "phase_number": "integer (1-7)",
  "phase_name": "string",
  "status": "not_started | in_progress | completed | blocked",
  "start_date": "ISO 8601 datetime or null",
  "end_date": "ISO 8601 datetime or null",
  "primary_driver": "role name",
  "completion_percentage": "integer (0-100)",
  "key_activities": "array",
  "deliverables": "array",
  "blockers": "array",
  "notes": "string"
}

Sprint Schema

{
  "sprint_id": "string (unique)",
  "sprint_name": "string",
  "project_name": "string",
  "phase_number": "integer",
  "start_date": "ISO 8601 datetime",
  "end_date": "ISO 8601 datetime",
  "status": "planning | active | completed | cancelled",
  "tasks": [
    {
      "task_id": "string",
      "description": "string",
      "assignee": "string",
      "status": "todo | in_progress | done | blocked",
      "story_points": "integer"
    }
  ],
  "velocity": "integer",
  "burn_down": "array of daily progress",
  "retrospective": "string"
}

Web UI Specification

Dashboard View

• Project List: Grid/table showing all active projects
  • Project name, current phase, progress bar, last updated
  • Quick status indicators (on-track, at-risk, blocked)
  • Click to drill into project details

Project Detail View

• Phase Timeline: Visual representation of 7 phases
  • Current phase highlighted
  • Progress indicators for each phase
  • Phase transition history
• Sprint Board: Current and recent sprints
  • Sprint velocity charts
  • Task completion status
  • Blocker alerts
• Activity Log: Chronological updates
  • Phase transitions
  • Major milestones
  • Team updates

Progress Tracking View

• Burn-down Charts: Sprint and phase level
• Velocity Trends: Historical sprint velocity
• Phase Completion Matrix: Cross-project phase status
• Team Utilization: Role involvement across projects

Interaction Features

• Quick Actions:
  • Update phase status
  • Create new sprint
  • Log blocker
  • Transition to next phase
• Filters:
  • By project status
  • By phase
  • By role involvement
  • By date range
• Export Options:
  • Project reports (PDF/CSV)
  • Timeline visualizations
  • Progress metrics

Implementation Requirements

Technology Stack

• Server: Node.js/TypeScript MCP server
• Storage: SQLite for persistence (or JSON file storage for simplicity)
• UI Framework: React/Next.js for web interface
• Visualization: Chart.js or D3.js for progress charts
• API: RESTful endpoints for UI communication

File Structure

mcp-pdl/
├── src/
│   ├── server.ts           # Main MCP server
│   ├── handlers/           # Function handlers
│   ├── models/            # Data models
│   ├── storage/           # Database/file operations
│   └── agent-profiles/    # Role profile definitions
├── ui/
│   ├── pages/             # Next.js pages
│   ├── components/        # React components
│   ├── api/              # API routes
│   └── styles/           # CSS/styling
├── CLAUDE.md             # Agent usage instructions
├── package.json
├── tsconfig.json
└── README.md

Usage Instructions for Claude Code

1. Initialize the MCP server structure with TypeScript support
2. Create agent profiles in .claude/agents/ directory for all 7 roles based on the provided templates
3. Implement core functions following the MCP protocol specification
4. Set up data persistence using SQLite or JSON file storage
5. Build the web UI with project dashboard and progress tracking
6. Create the .claude/CLAUDE.md file with detailed instructions for AI agents on how to:
   • Initialize projects
   • Track phase progression
   • Manage sprints
   • Collaborate based on role profiles
   • Interpret progress metrics
   • Handle phase transitions
   • Resolve blockers

CLAUDE.md Specification

The .claude/CLAUDE.md file must serve as the primary instruction set that all agents inherit. It should include:

MCP Protocol Interface Instructions

• How to call each mcp__pdl__ function with proper syntax
• When to use each function in the context of PDL phases
• Error handling and retry logic for failed calls
• Required parameters vs optional parameters for each function

Documentation Standards

• Template for project documentation updates
• Required fields for activity logs
• Format for recording blockers and resolutions
• Sprint retrospective documentation format
• Phase transition documentation requirements

Behavioral Guidelines

• Conciseness: Communicate efficiently without sacrificing clarity
• Accuracy: Never report false completions or fabricate data
• Verification: Always check actual status before reporting
• Documentation: Log all significant actions and decisions
• Collaboration: Reference other agents' profiles when coordinating

Project CLAUDE.md Updates

Each project should maintain its own CLAUDE.md log containing:

• Important documents and their locations
• Key decisions and rationale
• Milestone achievements
• Blocker resolutions
• Team changes or role reassignments
• Lessons learned per phase

Success Criteria

• [ ] Multi-project support with isolated contexts
• [ ] Full CRUD operations for phases and sprints
• [ ] Role-based agent profiles accessible via MCP
• [ ] Persistent storage of project state
• [ ] Web UI for visual progress tracking
• [ ] Comprehensive activity logging
• [ ] Phase transition automation
• [ ] Sprint velocity tracking
• [ ] Blocker management system
• [ ] Export capabilities for reporting

Extension Possibilities

• Integration with external project management tools (Jira, Asana)
• Automated phase transition recommendations
• AI-powered blocker resolution suggestions
• Team performance analytics
• Resource allocation optimization
• Risk assessment based on phase progress
• Stakeholder notification system
• Template library for common project types