Mentioned as a potential future integration for connecting with external project management tools to enhance product development lifecycle tracking
Used for creating progress charts, burn-down charts, velocity trends, and other data visualizations in the web UI
Mentioned as a potential future integration for connecting with external project management tools to enhance product development lifecycle tracking
Powers the web UI framework for the project dashboard, progress tracking views, and interactive project management interface
Provides the component framework for building the web interface including project dashboards, sprint boards, and progress tracking views
Provides persistent storage for project data, phase information, sprint tracking, and activity logs
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:
- Discovery & Ideation - Problem validation and idea generation
- Definition & Scoping - Requirements and planning
- Design & Prototyping - UX/UI design and testing
- Development & Implementation - Code construction
- Testing & Quality Assurance - Quality verification
- Launch & Deployment - Release management
- 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
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 identifierinclude_sprints
(boolean, optional): Include sprint details in response
Returns:
2. update_phase
Updates phase status and details for a project.
Parameters:
project_name
(string, required): Unique project identifierphase_number
(integer, optional): Phase to update (1-7), defaults to currentstatus
(string, optional): "not_started" | "in_progress" | "completed" | "blocked"completion_percentage
(integer, optional): 0-100notes
(string, optional): Update notes or blockerstransition_to_next
(boolean, optional): Auto-transition to next phase if current is completed
Returns:
3. track_progress
Records and retrieves progress updates for sprints within phases.
Parameters:
project_name
(string, required): Unique project identifieraction
(string, required): "create_sprint" | "update_sprint" | "get_sprints" | "get_timeline"sprint_data
(object, conditional): Required for create/update actionssprint_name
(string): Sprint identifierphase_number
(integer): Associated phase (1-7)tasks
(array): Task list with statusvelocity
(integer): Story points or task completion rateblockers
(array): Current impediments
Returns:
4. initialize_project
Creates a new project with PDL phase structure.
Parameters:
project_name
(string, required): Unique project identifierdescription
(string, optional): Project descriptionteam_composition
(object, optional): Role assignmentsstart_phase
(integer, optional): Starting phase (default: 1)
Returns:
Data Storage Structure
Project Schema
Phase Schema
Sprint Schema
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
Usage Instructions for Claude Code
- Initialize the MCP server structure with TypeScript support
- Create agent profiles in
.claude/agents/
directory for all 7 roles based on the provided templates - Implement core functions following the MCP protocol specification
- Set up data persistence using SQLite or JSON file storage
- Build the web UI with project dashboard and progress tracking
- 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
This server cannot be installed
local-only server
The server can only run on the client's local machine because it depends on local resources.
Enables AI agents to track and manage product development projects through structured 7-phase lifecycles with sprint tracking, role-based collaboration, and multi-project support. Provides phase management, progress tracking, and team coordination tools for complete product development workflows.