MCP GitHub Project Manager

A comprehensive Model Context Protocol (MCP) server that provides advanced GitHub project management capabilities with AI-powered task management and complete requirements traceability. Transform your project ideas into actionable tasks with full end-to-end tracking from business requirements to implementation.


Overview

This server implements the Model Context Protocol to provide comprehensive GitHub project management with advanced AI capabilities. Beyond traditional project management, it offers AI-powered task generation, requirements traceability, and intelligent project planning through GitHub's GraphQL API while maintaining state and handling errors according to MCP specifications.

$3

- AI-Powered: Transform project ideas into comprehensive PRDs and actionable tasks using multiple AI providers
- Complete Traceability: Full end-to-end tracking from business requirements → features → use cases → tasks
- Intelligent Analysis: AI-powered complexity analysis, effort estimation, and task recommendations
- Professional Standards: IEEE 830 compliant requirements documentation with enterprise-grade change management

Table of Contents

- Overview
- Quick Start
- Key Features
- Installation
- Configuration
- Usage
- As a command-line tool
- Running from source with TypeScript
- As a Node.js module
- Integration with MCP clients
- Installing in AI Assistants
- Claude
- Roocode
- Windsurf
- VS Code
- Cursor
- Using Docker
- Troubleshooting
- Architecture
- Contributing
- License
- References
- Current Status

Quick Start

$3

``bash

Install the package globally

npm install -g mcp-github-project-manager

Set up your environment variables

export GITHUB_TOKEN="your_github_token"
export GITHUB_OWNER="your_github_username_or_organization"
export GITHUB_REPO="your_repository_name"

Run the MCP server

mcp-github-project-manager
`

$3

`bash

Build the Docker image

docker build -t mcp-github-project-manager .

Run with environment variables

docker run -it \
-e GITHUB_TOKEN=your_github_token \
-e GITHUB_OWNER=your_github_username_or_organization \
-e GITHUB_REPO=your_repository_name \
mcp-github-project-manager
`

For more details on Docker usage, see DOCKER.md.

Key Features

$3

- PRD Generation (generate_prd): Transform project ideas into comprehensive Product Requirements Documents
- Intelligent Task Breakdown (parse_prd): AI-powered parsing of PRDs into actionable development tasks
- Smart Feature Addition (add_feature): Add new features with automatic impact analysis and task generation
- Task Complexity Analysis (analyze_task_complexity): Detailed AI analysis of task complexity, effort estimation, and risk assessment
- Next Task Recommendations (get_next_task): AI-powered recommendations for optimal task prioritization
- Task Expansion (expand_task): Break down complex tasks into manageable subtasks automatically
- PRD Enhancement (enhance_prd): Improve existing PRDs with AI-powered gap analysis and improvements

$3

- Traceability-Based Context (Default): Rich context from requirements traceability without AI dependency
- AI-Enhanced Context (Optional): Comprehensive business, technical, and implementation context using AI
- Configurable Context Levels: Choose between minimal, standard, and full context depth
- Business Context: Extract business objectives, user impact, and success metrics
- Technical Context: Analyze technical constraints, architecture decisions, and integration points
- Implementation Guidance: AI-generated step-by-step implementation recommendations
- Contextual References: Links to relevant PRD sections, features, and technical specifications
- Enhanced Acceptance Criteria: Detailed, testable criteria with verification methods
- Graceful Degradation: Works perfectly without AI keys, falls back to traceability-based context

$3

- End-to-End Tracking (create_traceability_matrix): Full traceability from PRD business requirements → features → use cases → tasks
- Bidirectional Links: Complete bidirectional traceability with impact analysis
- Use Case Management: Professional actor-goal-scenario use case generation and tracking
- Coverage Analysis: Comprehensive coverage metrics with gap identification
- Orphaned Task Detection: Identify tasks without requirements links
- Change Impact Analysis: Track requirement changes and their impact across all levels

$3

- Anthropic Claude: Primary AI provider for complex reasoning
- OpenAI GPT: Alternative provider with fallback support
- Google Gemini: Additional AI capabilities
- Perplexity: Research and analysis tasks
- Automatic Fallback: Seamless switching between providers

$3

- Project Management: Create and manage GitHub Projects (v2)
- Issues and Milestones: Full CRUD operations with advanced filtering
- Sprint Planning: Plan and manage development sprints with AI assistance
- Custom Fields and Views: Create different views (board, table, timeline, roadmap)
- Resource Versioning: Intelligent caching and optimistic locking

$3

- MCP Implementation: Full MCP specification compliance with Zod validation
- GitHub Integration: GraphQL API integration with intelligent rate limiting
- Real-time Sync: Bidirectional synchronization with GitHub
- Webhook Integration: Real-time updates via GitHub webhooks
- Progress Tracking: Comprehensive metrics and progress reporting
- Event System: Track and replay project events

Installation

$3

`bash


Install the package globally

npm install -g mcp-github-project-manager

Or install in your project

npm install mcp-github-project-manager
`

$3

`bash


Clone the repository

git clone https://github.com/kunwarVivek/mcp-github-project-manager.git
cd mcp-github-project-manager

Install dependencies

npm install

or

pnpm install

Build the project

npm run build
`

$3

`bash


Copy the example environment file

cp .env.example .env

Edit .env with your GitHub token and details

`

Configuration

$3

#### GitHub Configuration
`env
GITHUB_TOKEN=your_github_token
GITHUB_OWNER=repository_owner
GITHUB_REPO=repository_name
`

The GitHub token requires these permissions:
- repo (Full repository access)
- project (Project access)
- write:org (Organization access)

#### AI Provider Configuration
At least one AI provider is required for AI-powered features:

`env


Primary AI providers (at least one required)

ANTHROPIC_API_KEY=your_anthropic_api_key_here
OPENAI_API_KEY=your_openai_api_key_here
GOOGLE_API_KEY=your_google_api_key_here
PERPLEXITY_API_KEY=your_perplexity_api_key_here

AI Model Configuration (optional - uses defaults if not specified)

AI_MAIN_MODEL=claude-3-5-sonnet-20241022
AI_RESEARCH_MODEL=perplexity-llama-3.1-sonar-large-128k-online
AI_FALLBACK_MODEL=gpt-4o
AI_PRD_MODEL=claude-3-5-sonnet-20241022

AI Task Generation Configuration (optional)

MAX_TASKS_PER_PRD=50
DEFAULT_COMPLEXITY_THRESHOLD=7
MAX_SUBTASK_DEPTH=3
AUTO_DEPENDENCY_DETECTION=true
AUTO_EFFORT_ESTIMATION=true

Enhanced Task Context Generation Configuration (optional)

ENHANCED_TASK_GENERATION=true
AUTO_CREATE_TRACEABILITY=true
AUTO_GENERATE_USE_CASES=true
AUTO_CREATE_LIFECYCLE=true
ENHANCED_CONTEXT_LEVEL=standard
INCLUDE_BUSINESS_CONTEXT=false
INCLUDE_TECHNICAL_CONTEXT=false
INCLUDE_IMPLEMENTATION_GUIDANCE=false
`

$3

#### Anthropic Claude
1. Sign up at Anthropic Console
2. Create an API key
3. Set ANTHROPIC_API_KEY in your environment

#### OpenAI
1. Sign up at OpenAI Platform
2. Create an API key
3. Set OPENAI_API_KEY in your environment

#### Google Gemini
1. Sign up at Google AI Studio
2. Create an API key
3. Set GOOGLE_API_KEY in your environment

#### Perplexity
1. Sign up at Perplexity API
2. Create an API key
3. Set PERPLEXITY_API_KEY in your environment

Usage

$3

If installed globally:

`bash


Start the MCP server using stdio transport

mcp-github-project-manager

Start with environment variables

GITHUB_TOKEN=your_token mcp-github-project-manager

Start with command line arguments

mcp-github-project-manager --token=your_token --owner=your_username --repo=your_repo

Use a specific .env file

mcp-github-project-manager --env-file=.env.production

Show verbose output

mcp-github-project-manager --verbose

Display help information

mcp-github-project-manager --help
`

$3

If you're developing or running from source:

`bash


Run directly with ts-node

node --loader ts-node/esm src/index.ts

Run with command line arguments

node --loader ts-node/esm src/index.ts --token=your_token --owner=your_username --repo=your_repo

Use the npm dev script (watches for changes)

npm run dev

Display help information

node --loader ts-node/esm src/index.ts --help
`

#### Command Line Options

| Option | Short | Description |
|--------|-------|-------------|
| --token | -t | GitHub personal access token |
| --owner | -o | GitHub repository owner (username or organization) |
| --repo | -r | GitHub repository name |
| --env-file | -e | Path to .env file (default: .env in project root) |
| --verbose | -v | Enable verbose logging |
| --help | -h | Display help information |
| --version | | Display version information |

Command line arguments take precedence over environment variables.

$3

`javascript
import { Server } from "mcp-github-project-manager";

// Create and start an MCP server instance
const server = new Server({
transport: "stdio", // or "http" for HTTP server
config: {
githubToken: process.env.GITHUB_TOKEN,
githubOwner: process.env.GITHUB_OWNER,
githubRepo: process.env.GITHUB_REPO
}
});

server.start();
`

$3

`javascript
// Example using an MCP client library
import { McpClient } from "@modelcontextprotocol/client";
import { spawn } from "child_process";

// Create a child process running the MCP server
const serverProcess = spawn("mcp-github-project-manager", [], {
env: { ...process.env, GITHUB_TOKEN: "your_token" }
});

// Connect the MCP client to the server
const client = new McpClient({
transport: {
type: "process",
process: serverProcess
}
});

// Call MCP tools
const result = await client.callTool("create_project", {
title: "My Project",
description: "A new GitHub project"
});
`

For more examples, see the User Guide and the examples/ directory.

$3

#### Complete Project Workflow
`bash


1. Generate PRD from project idea

generate_prd({
"projectIdea": "AI-powered task management system with real-time collaboration",
"projectName": "TaskAI Pro",
"author": "product-team",
"complexity": "high",
"timeline": "6 months",
"includeResearch": true
})

2. Parse PRD and generate tasks with traceability

parse_prd({
"prdContent": "",
"maxTasks": 30,
"createTraceabilityMatrix": true,
"includeUseCases": true,
"projectId": "task-ai-pro"
})

3. Get next task recommendations

get_next_task({
"sprintCapacity": 40,
"teamSkills": ["react", "node.js", "typescript"],
"maxComplexity": 7,
"includeAnalysis": true
})

4. Analyze complex tasks

analyze_task_complexity({
"taskTitle": "Implement real-time collaboration",
"taskDescription": "Build WebSocket-based real-time collaboration with conflict resolution",
"teamExperience": "mixed",
"includeBreakdown": true,
"includeRisks": true
})

5. Break down complex tasks

expand_task({
"taskTitle": "Build analytics dashboard",
"taskDescription": "Create comprehensive analytics dashboard with AI insights",
"currentComplexity": 8,
"targetComplexity": 3,
"includeEstimates": true,
"includeDependencies": true
})
`

#### Feature Addition Workflow
`bash


Add new feature with complete lifecycle

add_feature({
"featureIdea": "Advanced Analytics Dashboard",
"description": "Real-time analytics with custom charts and AI-powered insights",
"requestedBy": "product-manager",
"businessJustification": "Increase user engagement and provide actionable insights",
"targetUsers": ["project-managers", "team-leads", "executives"],
"autoApprove": true,
"expandToTasks": true,
"createLifecycle": true
})

This automatically creates:

✅ Business requirement analysis

✅ Use cases with actor-goal-scenario structure

✅ Tasks with complete traceability links

✅ Lifecycle tracking for all tasks

`

#### Requirements Traceability
`bash


Create comprehensive traceability matrix

create_traceability_matrix({
"projectId": "task-ai-pro",
"prdContent": "",
"features": [...],
"tasks": [...],
"validateCompleteness": true
})

Output includes:

✅ Business Requirements → Features → Use Cases → Tasks

✅ Bidirectional traceability links

✅ Coverage analysis with gap identification

✅ Orphaned task detection

✅ Unimplemented requirement tracking

`

#### Enhanced Task Context Generation
`bash


Default: Traceability-based context (fast, no AI required)

parse_prd({
"prdContent": "",
"enhancedGeneration": true,
"contextLevel": "standard"
})

Enhanced: AI-powered comprehensive context

parse_prd({
"prdContent": "",
"enhancedGeneration": true,
"contextLevel": "full",
"includeBusinessContext": true,
"includeTechnicalContext": true,
"includeImplementationGuidance": true
})

Performance optimized: Minimal context for speed

parse_prd({
"prdContent": "",
"enhancedGeneration": true,
"contextLevel": "minimal",
"includeBusinessContext": false,
"includeTechnicalContext": false,
"includeImplementationGuidance": false
})
`

Context Generation Levels:
- Minimal: Basic traceability context only (fastest)
- Standard: Traceability + basic business context (default)
- Full: Complete AI-enhanced context with implementation guidance

Generated Task Context Includes:
- Business Context: Why the task matters, user impact, success metrics
- Feature Context: Parent feature information, user stories, business value
- Technical Context: Constraints, architecture decisions, integration points
- Implementation Guidance: Step-by-step recommendations, best practices, pitfalls
- Enhanced Acceptance Criteria: Detailed verification methods and priorities
- Contextual References: Links to relevant PRD sections and technical specs

$3

The enhanced context generation functionality includes comprehensive test coverage:

#### Test Files Created:
- src/__tests__/TaskContextGenerationService.test.ts - Core context generation service tests
- src/__tests__/TaskGenerationService.enhanced.test.ts - Enhanced task generation integration tests
- src/__tests__/ParsePRDTool.enhanced.test.ts - Tool-level context generation tests

#### Test Coverage:
- Traceability-based context generation (default behavior)
- AI-enhanced context generation (when AI is available)
- Graceful fallback when AI services are unavailable
- Configuration validation and environment variable handling
- Error handling and resilience testing
- Integration testing with existing task generation pipeline

#### Running Context Generation Tests:
`bash


Run all AI-related tests (includes context generation)

npm run test:ai

Run specific context generation tests

npm test -- --testPathPattern="TaskContextGeneration"
npm test -- --testPathPattern="enhanced"

Run all tests

npm test
`

🧪 Comprehensive E2E Testing Suite

The MCP GitHub Project Manager includes a comprehensive end-to-end testing suite that tests all MCP tools through the actual MCP interface with both mocked and real API calls.

$3

- ✅ 40+ GitHub Project Management Tools - Complete CRUD operations for projects, milestones, issues, sprints, labels, and more
- ✅ 8 AI Task Management Tools - PRD generation, task parsing, complexity analysis, feature management, and traceability
- ✅ Complex Workflow Integration - Multi-tool workflows and real-world project management scenarios
- ✅ Real API Testing - Optional testing with actual GitHub and AI APIs
- ✅ Schema Validation - Comprehensive argument validation for all tools
- ✅ Error Handling - Graceful error handling and recovery testing

$3

`bash

Run comprehensive E2E tests (mocked APIs)

npm run test:e2e:tools

Run with real APIs (requires credentials)

npm run test:e2e:tools:real

Use the interactive test runner

npm run test:e2e:runner

Run specific test categories

npm run test:e2e:tools:github # GitHub tools only
npm run test:e2e:tools:ai # AI tools only
npm run test:e2e:tools:workflows # Integration workflows
`

$3

`bash

Interactive test runner with options

node scripts/run-e2e-tests.js --help

Examples:

node scripts/run-e2e-tests.js --real-api --github-only
node scripts/run-e2e-tests.js --build --verbose --timeout 120
node scripts/run-e2e-tests.js --ai-only --real-api
`

$3

GitHub API (Required for GitHub tools):
`bash
GITHUB_TOKEN=ghp_your_github_token
GITHUB_OWNER=your-github-username
GITHUB_REPO=your-test-repository
`

AI APIs (Required for AI tools):
`bash


At least one AI API key required


ANTHROPIC_API_KEY=sk-ant-your-anthropic-key
OPENAI_API_KEY=sk-your-openai-key
GOOGLE_API_KEY=your-google-ai-key
PERPLEXITY_API_KEY=pplx-your-perplexity-key
`

Enable Real API Testing:
`bash
E2E_REAL_API=true npm run test:e2e:tools:real
`

$3

- Tool Registration Validation - Verify all tools are properly registered with correct schemas
- MCP Protocol Compliance - Ensure all tools follow MCP specification
- Response Format Validation - Validate tool responses match expected formats
- Workflow Integration Testing - Test complex multi-tool workflows
- Credential Management - Graceful handling of missing credentials
- Performance Monitoring - Track tool execution performance
- Comprehensive Error Testing - Validate error handling and recovery

$3

- 📖 Comprehensive E2E Testing Guide - Detailed testing documentation
- 🔧 Test Configuration - Jest configuration for E2E tests
- 🛠️ Test Utilities - Reusable test utilities

The E2E test suite ensures that all MCP tools work correctly both individually and in complex workflows, providing confidence in the reliability and integration of the entire system.

#### Test Scenarios Covered:
- ✅ Default traceability-based context (no AI required)
- ✅ AI-enhanced business context generation
- ✅ AI-enhanced technical context generation
- ✅ Implementation guidance generation
- ✅ Context merging and conflict resolution
- ✅ Error handling and graceful degradation
- ✅ Configuration validation and defaults
- ✅ Tool-level parameter validation
- ✅ Integration with existing traceability system

$3

#### Install in Claude

To install the MCP server in Claude Desktop:

`json
{
"mcpServers": {
"github-project-manager": {
"command": "npx",
"args": ["-y", "mcp-github-project-manager"],
"env": {
"GITHUB_TOKEN": "your_github_token",
"GITHUB_OWNER": "your_username",
"GITHUB_REPO": "your_repo",
"ANTHROPIC_API_KEY": "your_anthropic_api_key",
"OPENAI_API_KEY": "your_openai_api_key",
"GOOGLE_API_KEY": "your_google_api_key",
"PERPLEXITY_API_KEY": "your_perplexity_api_key"
}
}
}
}
`

For Claude Code CLI, run:

`bash
claude mcp add github-project-manager -- npx -y mcp-github-project-manager
`

#### Install in Roocode

Add this to your Roocode configuration:

`json
{
"mcpServers": {
"github-project-manager": {
"command": "npx",
"args": ["-y", "mcp-github-project-manager"],
"env": {
"GITHUB_TOKEN": "your_github_token",
"GITHUB_OWNER": "your_username",
"GITHUB_REPO": "your_repo"
}
}
}
}
`

#### Install in Windsurf

Add this to your Windsurf MCP config file:

`json
{
"mcpServers": {
"github-project-manager": {
"command": "npx",
"args": ["-y", "mcp-github-project-manager"],
"env": {
"GITHUB_TOKEN": "your_github_token",
"GITHUB_OWNER": "your_username",
"GITHUB_REPO": "your_repo"
}
}
}
}
`

See Windsurf MCP docs for more information.

#### Install in VS Code

Add this to your VS Code MCP config file:

`json
{
"servers": {
"github-project-manager": {
"type": "stdio",
"command": "npx",
"args": ["-y", "mcp-github-project-manager"],
"env": {
"GITHUB_TOKEN": "your_github_token",
"GITHUB_OWNER": "your_username",
"GITHUB_REPO": "your_repo"
}
}
}
}
`

See VS Code MCP docs for more information.

#### Install in Cursor

Add this to your Cursor MCP config file:

`json
{
"mcpServers": {
"github-project-manager": {
"command": "npx",
"args": ["-y", "mcp-github-project-manager"],
"env": {
"GITHUB_TOKEN": "your_github_token",
"GITHUB_OWNER": "your_username",
"GITHUB_REPO": "your_repo"
}
}
}
}
`

See Cursor MCP docs for more information.

#### Using Docker

If you prefer to run the MCP server in a Docker container:

1. Build the Docker Image:

Create a Dockerfile in your project directory:

`dockerfile
FROM node:18-alpine

WORKDIR /app

# Install the package globally
RUN npm install -g mcp-github-project-manager

# Default command to run the server
CMD ["mcp-github-project-manager"]
`

Build the image:

`bash
docker build -t github-project-manager-mcp .
`

2. Configure Your MCP Client:

Update your MCP client's configuration to use the Docker command:

`json
{
"mcpServers": {
"github-project-manager": {
"command": "docker",
"args": ["run", "-i", "--rm", "github-project-manager-mcp"],
"env": {
"GITHUB_TOKEN": "your_github_token",
"GITHUB_OWNER": "your_username",
"GITHUB_REPO": "your_repo"
}
}
}
}
`

$3

#### Common Issues

1. Module Not Found Errors

If you encounter module resolution issues, try using bunx instead of npx:

`json
{
"mcpServers": {
"github-project-manager": {
"command": "bunx",
"args": ["-y", "mcp-github-project-manager"]
}
}
}
`

2. Windows-Specific Configuration

On Windows, you may need to use cmd to run the command:

`json
{
"mcpServers": {
"github-project-manager": {
"command": "cmd",
"args": [
"/c",
"npx",
"-y",
"mcp-github-project-manager"
]
}
}
}
`

3. Permission Issues

If you encounter permission issues, make sure your GitHub token has the required permissions listed in the Configuration section.

Architecture

The server follows Clean Architecture principles with distinct layers:

- Domain Layer: Core entities, repository interfaces, and Zod schemas
- Infrastructure Layer: GitHub API integration and implementations
- Service Layer: Business logic coordination
- MCP Layer: Tool definitions and request handling

See ARCHITECTURE.md for detailed architecture documentation.

Contributing

Contributions are welcome! Please see CONTRIBUTING.md for guidelines.

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Commit your changes: git commit -m 'Add some amazing feature'
4. Push to the branch: git push origin feature/amazing-feature
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

References

- Model Context Protocol
- GitHub Projects API
- Project Roadmap

Current Status

$3

| Feature | Status | Notes |
|---------|--------|-------|
| Project Creation | ✅ Complete | Full support for v2 projects |
| Milestone Management | ✅ Complete | CRUD operations implemented |
| Sprint Planning | ✅ Complete | Including metrics tracking |
| Issue Management | ✅ Complete | With custom fields support |
| Resource Versioning | ✅ Complete | With optimistic locking and schema validation |
| Webhook Integration | 📅 Planned | Real-time updates |

$3

| Feature | Status | Notes |
|---------|--------|-------|
| PRD Generation | ✅ Complete | Multi-provider AI support with comprehensive PRD creation |
| Task Generation | ✅ Complete | AI-powered parsing of PRDs into actionable tasks |
| Feature Addition | ✅ Complete | Smart feature addition with impact analysis |
| Task Complexity Analysis | ✅ Complete | Detailed AI analysis with risk assessment |
| Task Recommendations | ✅ Complete | AI-powered next task recommendations |
| Task Expansion | ✅ Complete | Break down complex tasks into subtasks |
| PRD Enhancement | ✅ Complete | AI-powered PRD improvement and gap analysis |
| Requirements Traceability | ✅ Complete | End-to-end traceability matrix with coverage analysis |

$3

| Feature | Status | Notes |
|---------|--------|-------|
| Business Requirements Extraction | ✅ Complete | Extract from PRD objectives and success metrics |
| Use Case Generation | ✅ Complete | Actor-goal-scenario structure with alternatives |
| Traceability Links | ✅ Complete | Bidirectional links with impact analysis |
| Coverage Analysis | ✅ Complete | Gap identification and orphaned task detection |
| Change Tracking | ✅ Complete | Requirement change impact analysis |
| Verification Tracking | ✅ Complete | Test case mapping and verification status |

$3

| Component | Status | Notes |
|-----------|--------|-------|
| Tool Definitions | ✅ Complete | All core tools implemented with Zod validation |
| Resource Management | ✅ Complete | Full CRUD operations with versioning |
| Security | ✅ Complete | Token validation and scope checking |
| Error Handling | ✅ Complete | According to MCP specifications |
| Transport | ✅ Complete | Stdio and HTTP support |

See STATUS.md for detailed implementation status.
| Resource Management | ✅ Complete | With optimistic locking and relationship tracking |
| Response Handling | ✅ Complete | Rich content formatting with multiple content types |
| Error Handling | ✅ Complete | Comprehensive error mapping to MCP error codes |
| State Management | ✅ Complete | With conflict resolution and rate limiting |

$3

- Enhanced Resource System:
- Added Zod schema validation for all resource types
- Implemented resource relationship tracking
- Created a centralized ResourceFactory for consistent resource access

- Improved GitHub API Integration:
- Added intelligent rate limiting with automatic throttling
- Implemented pagination support for REST and GraphQL APIs
- Enhanced error handling with specific error types

- Advanced Tool System:
- Created tool definition registry with Zod validation
- Implemented standardized tool response formatting
- Added example-based documentation for all tools

- Rich Response Formatting:
- Added support for multiple content types (JSON, Markdown, HTML, Text)
- Implemented progress updates for long-running operations
- Added pagination support for large result sets

$3

Despite the recent improvements, the following functional gaps still exist and are prioritized for future development:

1. Persistent Caching Strategy:
- While the ResourceCache provides in-memory caching, it lacks persistence across server restarts
- No distributed caching for multi-instance deployments
- Missing cache eviction policies for memory management

2. Real-time Event Processing:
- No webhook integration for real-time updates from GitHub
- Missing event-based subscription system for clients
- Lack of server-sent events (SSE) support for streaming updates

3. Advanced GitHub Projects v2 Features:
- Limited support for custom field types and validation
- Incomplete integration with GitHub's newer Projects v2 field types
- Missing automation rule management

4. Performance Optimization:
- No query batching for related resources
- Missing background refresh for frequently accessed resources
- Incomplete prefetching for related resources

5. Data Visualization and Reporting:
- No built-in visualization generators for metrics
- Missing report generation capabilities
- Limited time-series data analysis

See docs/mcp/gaps-analysis.md for detailed implementation status.

Documentation

- User Guide - Detailed usage instructions
- API Reference - Comprehensive tool documentation
- Tutorials - Step-by-step guides
- Examples - Code examples for common tasks
- Architecture - System architecture and design
- Contributing - Development guidelines
- MCP Documentation - MCP-specific details

$3

For an interactive exploration of the API, open the API Explorer in your browser.

Development

$3

`bash

Unit tests

npm test

Integration tests

npm run test:integration

End-to-end tests

npm run test:e2e
`

$3

`bash

Lint code

npm run lint

Type check

npm run type-check

Format code

npm run format
``

Contributing

We welcome contributions to the GitHub Project Manager MCP Server! Please see our Contributing Guide for details on:

- Development Workflow
- Code Standards
- Testing Guidelines
- Documentation Guidelines

License

MIT