Universal Infinite Loop MCP Server
About
A goal-agnostic parallel orchestration framework implementing Infinite Agentic Loop patterns as a Model Context Protocol (MCP) server.
Details
- Author
- gptprojectmanager
- Categories
- Developer Tools, AI, Automation
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Setup
Install Universal Infinite Loop MCP Server in your MCP client (Claude Desktop, Cursor, Windsurf, and others).
Repository: https://github.com/gptprojectmanager/universal-infinite-loop-mcp-server
Follow the installation instructions in the repository README, then restart your MCP client.
A goal-agnostic parallel orchestration framework implementing Infinite Agentic Loop patterns as a Model Context Protocol (MCP) server.
A goal-agnostic parallel orchestration framework implementing Disler's Infinite Agentic Loop patterns as a Model Context Protocol (MCP) server. This system enables sophisticated multi-agent coordination for any domain through specification-driven architecture.
- UI Components: React, Vue, Angular, Web Components
- Documentation: Technical docs, API references, tutorials, guides
- Code Generation: Functions, classes, modules, entire applications
- Research & Analysis: Data analysis, reports, investigations
- Content Creation: Articles, marketing copy, social media, blogs
- Design Systems: Component libraries, style guides, design tokens
- Wave-Based Generation: Parallel agent coordination with progressive sophistication
- Context Management: Intelligent context usage monitoring and graceful degradation
- Innovation Dimensions: Multi-dimensional creative exploration and uniqueness enforcement
- Quality Assurance: Domain-specific validation and quality scoring
- Failure Handling: Graceful error recovery and agent reassignment
- Flexible Specifications: Adapt to any domain through comprehensive specification system
- Progressive Sophistication: Multiple sophistication levels from basic to revolutionary
- Evolution Patterns: Linear, exponential, adaptive, and creative burst generation patterns
- Validation Rules: Customizable validation for syntax, semantics, functionality, and quality
# Clone and install git clone <repository-url> cd infinite-loop-mcp-server npm install # Build npm run build # Run in development npm run dev
{ "mcpServers": { "infinite-loop": { "command": "node", "args": ["/path/to/infinite-loop-mcp-server/dist/server.js"] } } }
Main orchestration tool for goal-agnostic parallel generation.
{ specification: UniversalSpecification, outputDirectory: string, mode: { type: 'SINGLE' | 'BATCH' | 'INFINITE', count: number | 'INFINITE', batchSize?: number, maxWaves?: number }, config?: { contextThreshold?: number, gracefulShutdown?: boolean, progressiveSophistication?: boolean } }
{ "specification": { "name": "React Search Components", "description": "Modern search interface components with various interaction patterns", "domain": { "category": "UI", "subcategory": "React Components", "targetAudience": "Frontend Developers", "complexity": "MODERATE" }, "outputRequirements": { "format": "tsx", "structure": "Single component file with TypeScript", "namingPattern": "SearchComponent_{number}.tsx", "qualityStandards": ["TypeScript compliant", "Accessible", "Responsive"] }, "innovationDimensions": ["interaction_patterns", "visual_design", "accessibility", "performance"], "sophisticationLevels": [...], "evolutionPattern": "CREATIVE_BURST" }, "outputDirectory": "./generated-components", "mode": { "type": "BATCH", "count": 10, "batchSize": 5 } }
{ "specification": { "name": "API Documentation", "description": "Comprehensive API documentation with examples and best practices", "domain": { "category": "DOCUMENTATION", "subcategory": "API Reference", "targetAudience": "Developers", "complexity": "COMPLEX" }, "outputRequirements": { "format": "md", "structure": "Structured markdown with code examples", "namingPattern": "api_docs_{number}.md", "qualityStandards": ["Complete coverage", "Clear examples", "Best practices"] }, "innovationDimensions": ["clarity", "completeness", "interactivity", "searchability"], "evolutionPattern": "LINEAR" }, "outputDirectory": "./docs", "mode": { "type": "INFINITE", "count": "INFINITE" } }
Plan generation waves with sophisticated agent assignment.
{ existingWork: IterationInfo[], sophisticationLevel: SophisticationLevel, targetCount: number, contextBudget: number }
Coordinate parallel agent execution with uniqueness enforcement.
{ assignments: AgentAssignment[], innovationDimensions: string[], contextMonitor: ContextMonitor }
Monitor context capacity and manage graceful shutdown.
{ waveId: string, capacityThreshold: number, gracefulShutdown: boolean }
Validate and enhance specifications with intelligent defaults.
{ userSpec: Partial<UniversalSpecification>, domain: SpecificationDomain, outputRequirements: any }
interface UniversalSpecification { id: string; name: string; description: string; domain: SpecificationDomain; version: string; outputRequirements: { format: string; structure: string; namingPattern: string; qualityStandards: string[]; }; innovationDimensions: string[]; sophisticationLevels: SophisticationLevel[]; constraints: string[]; evolutionPattern: 'LINEAR' | 'EXPONENTIAL' | 'ADAPTIVE' | 'CREATIVE_BURST'; progressionStrategy: string; successCriteria: string[]; validationRules: ValidationRule[]; }
- UI: Frontend components, interfaces, user experiences
- DOCUMENTATION: Technical writing, API docs, tutorials
- CODE: Functions, classes, modules, applications
- RESEARCH: Data analysis, investigations, reports
- CONTENT: Articles, marketing, social media
- ANALYSIS: Business analysis, performance reports
- DESIGN: Visual design, component libraries
- OTHER: Custom domains
- Basic: Fundamental functionality with core features
- Intermediate: Enhanced features with improved user experience
- Advanced: Sophisticated implementation with innovative approaches
- Revolutionary: Cutting-edge concepts pushing domain boundaries
- SINGLE: Generate one iteration
- BATCH: Generate specific number of iterations in coordinated batches
- INFINITE: Continuous generation until context limits with progressive sophistication
- Parallel Execution: Multiple agents working simultaneously with unique assignments
- Innovation Assignment: Each agent gets distinct innovation dimension to explore
- Context Management: Intelligent context usage tracking and optimization
- Quality Assurance: Real-time validation and quality scoring
- Uniqueness Enforcement: Prevention of duplicate concepts across parallel streams
Wave 1: Basic functional implementations Wave 2: Enhanced features and user experience Wave 3: Advanced concepts and innovative approaches Wave N: Revolutionary paradigm-defining implementations
// Detect when parallel generation is needed if (taskRequiresParallelGeneration(task)) { const specification = generateSpecificationFromTask(task); const result = await mcpClient.callTool('infinite_orchestrate', { specification, outputDirectory: task.outputDirectory, mode: { type: 'BATCH', count: task.iterationCount, batchSize: 5 } }); return integrateResultsIntoTask(result, task); }
// Define custom domain specification const customSpec: UniversalSpecification = { name: "Custom Data Analysis", domain: { category: "ANALYSIS", subcategory: "Financial Reports", targetAudience: "Business Analysts", complexity: "COMPLEX" }, innovationDimensions: [ "visualization_techniques", "data_insights", "predictive_modeling", "business_impact" ], // ... rest of specification };
- Real-time context usage tracking
- Graceful shutdown when approaching limits
- Wave-based context optimization
- Agent-specific context allocation
- Functionality compliance scoring
- Innovation uniqueness measurement
- Domain-specific quality validation
- Progressive improvement tracking
- Agent coordination efficiency
- Wave execution timing
- Resource utilization optimization
- Failure rate and recovery metrics
- Generate diverse component variations
- Explore different interaction patterns
- Create comprehensive design systems
- Test accessibility approaches
- Create multi-perspective documentation
- Generate comprehensive examples
- Explore different explanation styles
- Develop interactive documentation
- Generate alternative implementations
- Explore architectural patterns
- Create comprehensive test suites
- Develop optimization variations
- Explore multiple analysis angles
- Generate diverse visualization approaches
- Create comprehensive reports
- Investigate different methodologies
- Universal specification system
- Wave-based generation framework
- Agent coordination system
- Context management
- Machine learning-based quality prediction
- Dynamic specification evolution
- Cross-domain knowledge transfer
- Performance optimization
- IDE extensions and plugins
- Cloud deployment options
- Collaboration features
- Marketplace for specifications
Contributions are welcome! Please read our contributing guidelines and submit pull requests for any improvements.
MIT License - see LICENSE file for details.
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