🚀 SystemPrompt MCP TaskChecker

Enterprise-grade Model Context Protocol server for intelligent task management, evaluation scoring, and session-based workflow tracking.

Seamlessly integrates with AI assistants to provide structured task orchestration, real-time progress monitoring, and comprehensive evaluation metrics for next-generation AI-driven productivity solutions.

✨ What is SystemPrompt MCP TaskChecker?

The SystemPrompt MCP TaskChecker is a Model Context Protocol (MCP) server that transforms how AI assistants handle task management and workflow orchestration. Built by SystemPrompt.io, this enterprise-grade solution bridges the gap between AI intelligence and structured productivity workflows.

🎯 Key Value Propositions

🤖 AI-Native Task Management: Purpose-built for seamless integration with Claude, GPT, and other AI assistants
📊 Intelligent Evaluation Scoring: 0-100 scoring system with comprehensive metrics tracking
⚡ Session-Based Architecture: Stateful, secure, and automatically managed sessions
🏢 Enterprise-Ready: Production-grade reliability with comprehensive error handling
🔄 Real-Time Workflow Tracking: Live status updates and progress monitoring
🛡️ Secure & Compliant: Built-in validation, session management, and data integrity

🌟 Key Features

🎯 Intelligent Task Orchestration

Dynamic Task Lists: Create and manage sophisticated task hierarchies with optional initialization
Smart Status Tracking: Real-time status updates (pending → in_progress → completed)
Acceptance Criteria: Define clear, measurable completion requirements for each task
Flexible Updates: Modify any task property while maintaining data integrity

📈 Advanced Evaluation System

Precision Scoring: 0-100 evaluation scale for completed tasks
Quality Metrics: Track task completion quality and performance indicators
Historical Analysis: Maintain evaluation history for continuous improvement
Success Benchmarking: Compare and analyze task completion patterns

🔒 Enterprise Session Management

Stateful Operations: Maintain context across multiple interactions
Automatic Cleanup: Intelligent session timeout and resource management
Concurrent Support: Handle multiple simultaneous sessions
Security Validation: Built-in session ID validation and error handling

🚀 Production-Grade Architecture

MCP 2025-03-26 Compliant: Latest Model Context Protocol standards
Streamable HTTP Transport: High-performance, scalable communication
Structured Error Handling: Comprehensive error responses and logging
TypeScript Native: Full type safety and developer experience

🛠️ Installation & Setup

Prerequisites

Node.js: Version 18.0.0 or higher
npm: Latest stable version
TypeScript: Included in devDependencies

Quick Start

# Clone the repository git clone https://github.com/Ejb503/systemprompt-mcp-taskchecker.git cd systemprompt-mcp-taskchecker # Install dependencies npm install # Build the project npm run build # Start the server npm start

Development Environment

# Development mode with hot reload npm run dev # Run tests npm test # Run with coverage npm run test:coverage # Test client integration npm run test:client

Docker Deployment

# Build Docker image npm run docker:build # Run in container npm run docker:run

🎮 Usage Examples

Basic Task List Creation

{ "method": "tools/call", "params": { "name": "create_tasklist", "arguments": { "initialTasks": [ { "title": "Implement user authentication", "acceptanceCriteria": "User can login with email/password and receive JWT token" }, { "title": "Create dashboard UI", "acceptanceCriteria": "Responsive dashboard showing user metrics and navigation" } ] } } }

Task Status Updates

{ "method": "tools/call", "params": { "name": "update_task", "arguments": { "taskListId": "uuid-task-list-id", "taskId": "uuid-task-id", "updates": { "status": "completed", "evaluation": 95 } } } }

Comprehensive Status Retrieval

{ "method": "tools/call", "params": { "name": "get_status", "arguments": { "taskListId": "uuid-task-list-id" } } }

🔧 MCP Tools Reference

`create_tasklist`

Creates a new task list for the current session with optional initial tasks

Parameter	Type	Required	Description
`initialTasks`	`Array<Task>`	No	Array of initial tasks to create

Response Structure:

{ success: boolean; data: { id: string; sessionId: string; tasks: Task[]; createdAt: Date; lastAccessed: Date; } }

`update_task`

Updates specific task properties including status, evaluation, and metadata

Parameter	Type	Required	Description
`taskListId`	`string`	Yes	ID of the target task list
`taskId`	`string`	Yes	ID of the task to update
`updates`	`TaskUpdates`	Yes	Object containing properties to update

Available Updates:

title: Task title (string)
status: Task status (pending | in_progress | completed)
acceptanceCriteria: Completion criteria (string)
evaluation: Quality score (0-100)

`get_status`

Retrieves current status for all tasks or a specific task

Parameter	Type	Required	Description
`taskListId`	`string`	Yes	ID of the task list to query
`taskId`	`string`	No	Optional specific task ID

📊 Data Models

Task Structure

interface Task { id: string; // Unique task identifier title: string; // Task title/description status: TaskStatus; // Current task status acceptanceCriteria: string; // Completion requirements evaluation?: number; // Quality score (0-100) createdAt: Date; // Creation timestamp updatedAt: Date; // Last modification timestamp } type TaskStatus = 'pending' | 'in_progress' | 'completed';

TaskList Structure

interface TaskList { id: string; // Unique list identifier sessionId: string; // Associated session ID tasks: Task[]; // Array of tasks createdAt: Date; // Creation timestamp lastAccessed: Date; // Last access timestamp }

🏗️ Architecture Overview

System Components

┌─────────────────────────────────────────────────────────────┐ │ AI Assistant (Claude, GPT) │ └─────────────────────┬───────────────────────────────────────┘ │ MCP Protocol ┌─────────────────────▼───────────────────────────────────────┐ │ SystemPrompt MCP TaskChecker │ ├─────────────────────────────────────────────────────────────┤ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────────────┐ │ │ │ HTTP │ │ Session │ │ Task Service │ │ │ │ Transport │ │ Manager │ │ │ │ │ └─────────────┘ └─────────────┘ └─────────────────────┘ │ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────────────┐ │ │ │ Tool │ │ Config │ │ In-Memory Store │ │ │ │ Handlers │ │ Manager │ │ │ │ │ └─────────────┘ └─────────────┘ └─────────────────────┘ │ └─────────────────────────────────────────────────────────────┘

Technology Stack

Runtime: Node.js 18+
Language: TypeScript
Protocol: Model Context Protocol (MCP) 2025-03-26
Transport: Streamable HTTP
Storage: In-memory with automatic cleanup
Framework: Express.js
Package Manager: npm

🔒 Security & Compliance

Security Features

✅ Session Validation: Cryptographically secure session IDs
✅ Input Validation: Comprehensive parameter validation
✅ Error Handling: Structured error responses without information leakage
✅ Rate Limiting Ready: Architecture supports rate limiting implementation
✅ Transport Security: HTTPS/TLS support for production deployments

Compliance Standards

MCP Protocol Compliance: Fully compatible with MCP 2025-03-26
Data Privacy: In-memory storage with automatic cleanup
Enterprise Security: Session-based isolation and validation

📈 Performance & Scaling

Performance Characteristics

Memory Efficient: In-memory storage with intelligent cleanup
Low Latency: Sub-millisecond response times for typical operations
Concurrent Sessions: Supports 1000+ simultaneous sessions
Auto-Scaling Ready: Stateless architecture compatible with horizontal scaling

Resource Limits

Resource	Default Limit	Configurable
Max Tasks per List	100	✅
Max Task Lists	5	✅
Session Duration	5 minutes	✅
Concurrent Sessions	1000	✅
Evaluation Range	0-100	✅

🌐 Deployment Options

Production Deployment

# Environment variables export NODE_ENV=production export PORT=3000 export LOG_LEVEL=info # Start production server npm start

Docker Production

FROM node:18-alpine WORKDIR /app COPY . . RUN npm ci --only=production && npm run build EXPOSE 3000 CMD ["npm", "start"]

Cloud Integration

AWS: Compatible with ECS, Lambda, and EC2
Google Cloud: Supports Cloud Run, GKE, and Compute Engine
Azure: Works with Container Instances, AKS, and App Service
Railway/Vercel: One-click deployment ready

🧪 Testing & Quality Assurance

Test Coverage

# Unit tests npm test # Integration tests npm run test:client # Coverage report npm run test:coverage # Development testing npm run test:watch

Quality Tools

TypeScript: Full type safety and compile-time checks
ESLint: Code quality and consistency enforcement
Prettier: Automated code formatting
Jest: Comprehensive testing framework

📚 API Documentation

Health Check Endpoints

GET /health

Returns server health status and active session count.

GET /sessions

Lists active sessions (development/debugging).

DELETE /sessions/:sessionId

Manually cleanup specific session (testing).

MCP Endpoint

POST /mcp

Main MCP protocol endpoint for tool interactions.

🤝 Integration Examples

Claude Desktop Integration

Add to your Claude Desktop configuration:

{ "mcpServers": { "systemprompt-taskchecker": { "command": "npx", "args": ["systemprompt-mcp-taskchecker"], "env": { "NODE_ENV": "production" } } } }

Custom AI Assistant Integration

import { MCPClient } from '@modelcontextprotocol/sdk/client/index.js'; const client = new MCPClient({ transport: new HTTPClientTransport('http://localhost:3000/mcp') }); // Create task list const result = await client.callTool('create_tasklist', { initialTasks: [ { title: 'Setup development environment', acceptanceCriteria: 'All dependencies installed and tests passing' } ] });

🎯 Use Cases

🔧 Development Workflows

Track coding tasks and milestones
Manage code review requirements
Monitor deployment checklists
Evaluate task completion quality

📋 Project Management

Structure project deliverables
Track acceptance criteria compliance
Generate progress reports
Maintain quality benchmarks

🏢 Enterprise Operations

Standardize workflow processes
Implement quality gates
Track team performance metrics
Automate task orchestration

🤖 AI Assistant Enhancement

Provide structured task context
Enable persistent workflow memory
Support complex multi-step processes
Facilitate evaluation and improvement

🛠️ Development & Contributing

Development Setup

# Fork and clone the repository git clone https://github.com/YOUR_USERNAME/systemprompt-mcp-taskchecker.git cd systemprompt-mcp-taskchecker # Install dependencies npm install # Start development server npm run dev # Run tests in watch mode npm run test:watch

Code Quality Standards

TypeScript: Strict mode enabled
ESLint: Airbnb configuration with custom rules
Prettier: Consistent code formatting
Jest: Minimum 80% test coverage
Conventional Commits: Standardized commit messages

📊 Monitoring & Observability

Built-in Monitoring

Health Checks: /health endpoint with detailed status
Session Tracking: Real-time active session monitoring
Performance Metrics: Request/response timing and success rates
Error Tracking: Structured error logging with session context

Logging Configuration

# Set log level export LOG_LEVEL=debug # debug, info, warn, error # Enable structured logging export STRUCTURED_LOGS=true

🌟 Why SystemPrompt.io?

SystemPrompt.io is at the forefront of AI productivity innovation, creating enterprise-grade solutions that seamlessly bridge human intelligence with artificial intelligence. Our MCP TaskChecker represents our commitment to:

🚀 Innovation: Cutting-edge AI integration technologies
🏢 Enterprise Focus: Production-ready, scalable solutions
🔒 Security First: Built-in security and compliance features
🌐 Open Standards: Full Model Context Protocol compliance
💡 Developer Experience: Intuitive APIs and comprehensive documentation

Our Mission

Empowering organizations to harness the full potential of AI through intelligent workflow orchestration and productivity solutions.

📞 Support & Resources

🔗 Quick Links

🏠 Homepage: https://systemprompt.io
📖 Documentation: https://systemprompt.io/docs/mcp-taskchecker
💬 Support: https://systemprompt.io/support
🐛 Issues: GitHub Issues
📧 Contact: ed@tyingshoelaces.com

🤝 Community

GitHub Discussions: Share ideas and ask questions
Discord Server: Real-time community support (coming soon)
Blog: Latest updates and tutorials at systemprompt.io/blog

📄 License

MIT License

Copyright 2025 SystemPrompt.io Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

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Transforming AI productivity, one workflow at a time.