Multi Agent Orchestrator MCP

openapi: 3.0.3 info: title: Multi-Agent Orchestrator MCP Server - Revolutionary Edition description: | **🚀 REVOLUTIONARY MULTI-AGENT ORCHESTRATOR MCP SERVER 🚀** A cutting-edge Model Context Protocol (MCP) server featuring **5 LEGENDARY AI AGENTS** that transform software development through autonomous intelligence and revolutionary capabilities. **🌟 LEGENDARY AGENTS:** 1. **🏗️ Autonomous Architect Agent** - Self-evolving system architecture with dynamic DAG generation 2. **🛡️ Proactive Quality Framework** - Policy-as-code quality assurance with predictive analysis 3. **🧬 Evolutionary Prompt Engine** - Self-improving prompts with genetic algorithms 4. **☁️ Last Mile Cloud Agent** - Autonomous deployment across AWS, Azure, GCP with verification 5. **🎯 Legendary Application Generator** - Orchestrates all agents for revolutionary app creation **🔥 REVOLUTIONARY FEATURES:** - 🤖 Multi-Agent System (Frontend, Backend, DevOps, Reviewer + 4 Legendary Agents) - 🔄 Autonomous Self-Healing with LLM-powered failure analysis and auto-recovery - 🔐 Descope OAuth 2.1 + PKCE Authentication with Non-Human Identity support - 📊 Cequence AI Gateway Integration for real-time analytics and security monitoring - 🛠️ Full MCP Protocol Compliance (JSON-RPC 2.0) with legendary tool extensions - 🚀 Revolutionary Code Generation with architectural evolution and quality policies - 🧠 Self-Improving Intelligence through evolutionary prompt optimization - ☁️ Multi-Cloud Deployment Automation with autonomous verification **💡 COMPETITION INNOVATION:** This MCP server represents the pinnacle of autonomous software development by introducing revolutionary AI agents that not only generate applications but continuously evolve their own capabilities. The system demonstrates true intelligence through self-improvement, predictive quality assurance, and autonomous cloud orchestration. version: 3.0.0-LEGENDARY contact: name: Revolutionary AI Systems url: https://github.com/yoriichi-07/Multi_Orchestrator_MCP email: legendary@ai-systems.dev license: name: MIT Revolutionary License url: https://opensource.org/licenses/MIT servers: - url: https://server.smithery.ai/@yoriichi-07/multi_orchestrator_mcp/mcp description: Production server on Smithery (revolutionary competition deployment) - url: http://localhost:8080 description: Local development server with legendary capabilities security: - DescopeBearer: [] paths: # === LEGENDARY TOOLS - REVOLUTIONARY CAPABILITIES === /mcp/v3/legendary/generate_application: post: summary: 🎯 Legendary Application Generator description: | **🚀 REVOLUTIONARY APPLICATION GENERATION** The ultimate autonomous application generator that orchestrates all 4 legendary agents plus the core multi-agent system to create revolutionary applications with: - **Autonomous Architecture**: Self-evolving system design with dynamic DAG optimization - **Proactive Quality**: Policy-as-code with predictive issue prevention - **Evolutionary Prompts**: Self-improving generation through genetic algorithms - **Cloud-Native Deployment**: Multi-cloud autonomous deployment with verification - **Continuous Evolution**: Applications that improve themselves over time This represents the pinnacle of autonomous software development. tags: [🌟 Legendary Tools] requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/LegendaryGenerateApplicationRequest' responses: '200': description: Revolutionary application generated with legendary capabilities content: application/json: schema: $ref: '#/components/schemas/LegendaryGenerateApplicationResponse' /mcp/v3/legendary/autonomous_architect: post: summary: 🏗️ Autonomous Architect Agent description: | **🏗️ SELF-EVOLVING ARCHITECTURAL INTELLIGENCE** The Autonomous Architect Agent creates and evolves system architectures using: - **Dynamic DAG Generation**: Creates optimal dependency graphs that adapt to requirements - **Architectural Evolution**: Continuously improves designs based on performance feedback - **Pattern Recognition**: Learns from successful architectures to optimize future designs - **Constraint Optimization**: Balances performance, cost, and maintainability automatically - **Future-Proofing**: Designs systems that adapt to changing requirements This agent represents autonomous architectural intelligence that surpasses human capabilities. tags: [🌟 Legendary Tools] requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/AutonomousArchitectRequest' responses: '200': description: Revolutionary architecture generated with evolutionary capabilities content: application/json: schema: $ref: '#/components/schemas/AutonomousArchitectResponse' /mcp/v3/legendary/proactive_quality_assurance: post: summary: 🛡️ Proactive Quality Framework description: | **🛡️ PREDICTIVE QUALITY INTELLIGENCE** The Proactive Quality Framework revolutionizes software quality through: - **Policy-as-Code**: Automated quality policies that evolve with codebase - **Predictive Analysis**: Identifies potential issues before they manifest - **Continuous Improvement**: Learns from past issues to prevent future problems - **Multi-Dimensional Quality**: Security, performance, maintainability, and innovation metrics - **Autonomous Remediation**: Automatically applies fixes based on policy violations This framework ensures legendary quality that improves autonomously over time. tags: [🌟 Legendary Tools] requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/ProactiveQualityRequest' responses: '200': description: Comprehensive quality analysis with proactive recommendations content: application/json: schema: $ref: '#/components/schemas/ProactiveQualityResponse' /mcp/v3/legendary/evolutionary_prompt_optimization: post: summary: 🧬 Evolutionary Prompt Engine description: | **🧬 SELF-IMPROVING PROMPT INTELLIGENCE** The Evolutionary Prompt Engine creates and evolves prompts using: - **Genetic Algorithms**: Evolves prompts through selection, crossover, and mutation - **Performance Feedback**: Learns from execution results to improve effectiveness - **Multi-Objective Optimization**: Balances accuracy, creativity, and efficiency - **Adaptive Learning**: Adjusts strategies based on domain and context - **Continuous Evolution**: Prompts become more effective over time autonomously This engine demonstrates true AI self-improvement capabilities. tags: [🌟 Legendary Tools] requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/EvolutionaryPromptRequest' responses: '200': description: Optimized prompts with evolutionary improvements content: application/json: schema: $ref: '#/components/schemas/EvolutionaryPromptResponse' /mcp/v3/legendary/last_mile_cloud_deployment: post: summary: ☁️ Last Mile Cloud Agent description: | **☁️ AUTONOMOUS MULTI-CLOUD ORCHESTRATION** The Last Mile Cloud Agent provides revolutionary cloud deployment through: - **Multi-Cloud Intelligence**: Automatically selects optimal cloud providers and regions - **Autonomous Verification**: Validates deployments and performance automatically - **Cost Optimization**: Dynamically optimizes cloud resources for minimum cost - **Zero-Downtime Deployments**: Ensures continuous availability during updates - **Self-Healing Infrastructure**: Automatically recovers from infrastructure failures This agent transforms cloud deployment into an autonomous, intelligent process. tags: [🌟 Legendary Tools] requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/LastMileCloudRequest' responses: '200': description: Autonomous cloud deployment with multi-provider orchestration content: application/json: schema: $ref: '#/components/schemas/LastMileCloudResponse' # === CORE MCP PROTOCOL ENDPOINTS === /health: get: summary: Health Check with Legendary Status description: Enhanced health check including legendary agent status and revolutionary capabilities tags: [Health & Status] security: [] responses: '200': description: Server is healthy with legendary capabilities active content: application/json: schema: $ref: '#/components/schemas/HealthResponse' /mcp/initialize: post: summary: MCP Initialization with Legendary Capabilities description: Initialize MCP client-server connection with legendary agent capability negotiation tags: [MCP Protocol] requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/MCPInitializeRequest' responses: '200': description: Initialization successful with legendary capabilities enabled content: application/json: schema: $ref: '#/components/schemas/MCPInitializeResponse' /mcp/tools/list: post: summary: List All MCP Tools (Including Legendary) description: Get comprehensive list of all available MCP tools including legendary agents tags: [MCP Tools] requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/MCPListRequest' responses: '200': description: Complete list of tools including legendary capabilities content: application/json: schema: $ref: '#/components/schemas/MCPToolsListResponse' /mcp/tools/call: post: summary: Execute MCP Tool (Core + Legendary) description: Execute any MCP tool including legendary agents with full capability support tags: [MCP Tools] requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/MCPToolCallRequest' responses: '200': description: Tool execution result with legendary enhancement content: application/json: schema: $ref: '#/components/schemas/MCPToolCallResponse' # === CORE AGENT TOOLS === /mcp/v1/tools/orchestrate_task: post: summary: Multi-Agent Task Orchestration description: Orchestrate complex tasks across multiple specialized AI agents tags: [Core Agent Tools] requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/OrchestateTaskRequest' responses: '200': description: Task orchestrated successfully across agents content: application/json: schema: $ref: '#/components/schemas/OrchestateTaskResponse' /mcp/v1/tools/generate_architecture: post: summary: AI-Powered Architecture Generation description: Generate comprehensive system architecture using AI analysis tags: [Core Agent Tools] requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/GenerateArchitectureRequest' responses: '200': description: Architecture generated successfully content: application/json: schema: $ref: '#/components/schemas/GenerateArchitectureResponse' /mcp/v1/tools/auto_fix_code: post: summary: Autonomous Code Fixing description: Automatically fix code issues using self-healing capabilities tags: [Core Agent Tools] requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/AutoFixCodeRequest' responses: '200': description: Code fixed successfully content: application/json: schema: $ref: '#/components/schemas/AutoFixCodeResponse' # === INFRASTRUCTURE TOOLS === /mcp/v1/tools/ping: post: summary: Enhanced Connectivity Test description: Advanced ping with scope validation and legendary status tags: [Infrastructure] requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/PingRequest' responses: '200': description: Ping successful with enhanced information content: application/json: schema: $ref: '#/components/schemas/PingResponse' /mcp/v1/tools/get_system_status: post: summary: Comprehensive System Status description: Detailed system status including legendary agents and revolutionary metrics tags: [Infrastructure] requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/SystemStatusRequest' responses: '200': description: Comprehensive system status with legendary insights content: application/json: schema: $ref: '#/components/schemas/SystemStatusResponse' /mcp/v1/tools/list_capabilities: post: summary: List All System Capabilities description: Comprehensive list of all system capabilities including legendary features tags: [Infrastructure] requestBody: required: true content: application/json: schema: type: object properties: include_legendary: type: boolean default: true responses: '200': description: Complete capability list content: application/json: schema: $ref: '#/components/schemas/CapabilitiesResponse' # === ANALYTICS & MONITORING === /dashboard/legendary: get: summary: Legendary Analytics Dashboard description: Advanced Cequence AI Gateway analytics dashboard with legendary agent metrics tags: [Analytics & Monitoring] responses: '200': description: Enhanced analytics dashboard with legendary insights content: text/html: schema: type: string components: securitySchemes: DescopeBearer: type: http scheme: bearer bearerFormat: JWT description: | Descope OAuth 2.1 + PKCE JWT token with Non-Human Identity support for revolutionary capabilities. **Required Scopes for Legendary Tools:** - `legendary:architect` - Autonomous architecture generation and evolution - `legendary:quality` - Proactive quality assurance and policy management - `legendary:prompts` - Evolutionary prompt optimization and self-improvement - `legendary:cloud` - Last mile cloud deployment and multi-provider orchestration - `legendary:generate` - Complete revolutionary application generation - `tools:*` - All core MCP tools - `admin:*` - Administrative and monitoring capabilities schemas: # === LEGENDARY TOOL SCHEMAS === LegendaryGenerateApplicationRequest: type: object required: - description properties: description: type: string description: Detailed description of the revolutionary application to create example: "Create a next-generation social media platform with AI-powered content curation, real-time collaboration, and autonomous scaling" complexity_level: type: string enum: [simple, advanced, enterprise, revolutionary] default: revolutionary description: Target complexity level for the application innovation_requirements: type: array items: type: string example: ["AI-powered UX", "autonomous scaling", "predictive analytics", "self-healing infrastructure"] description: List of innovative features to include deployment_strategy: type: string enum: [local, cloud-native, multi-cloud, edge, revolutionary] default: revolutionary description: Deployment approach with autonomous optimization evolutionary_goals: type: array items: type: string example: ["continuous self-improvement", "adaptive user experience", "autonomous feature development"] description: Long-term evolutionary goals for the application quality_policies: type: object properties: security_level: type: string enum: [standard, high, revolutionary] default: revolutionary performance_targets: type: object properties: response_time_ms: type: integer example: 50 throughput_rps: type: integer example: 10000 maintainability_score: type: number format: float minimum: 8.0 maximum: 10.0 example: 9.5 LegendaryGenerateApplicationResponse: type: object properties: success: type: boolean example: true revolutionary_features: type: array items: type: string example: ["autonomous architecture evolution", "predictive quality assurance", "self-improving prompts", "multi-cloud orchestration"] autonomous_architecture: type: object properties: dag_structure: type: object description: Dynamic dependency graph structure optimization_metrics: type: object properties: performance_score: type: number format: float example: 9.7 maintainability_score: type: number format: float example: 9.3 innovation_score: type: number format: float example: 9.8 proactive_quality_policies: type: array items: type: object properties: policy_name: type: string example: "security_predictive_analysis" enforcement_level: type: string enum: [warning, error, blocking] success_rate: type: number format: float example: 0.95 evolutionary_prompts: type: object properties: generation_1_prompts: type: integer example: 50 optimized_prompts: type: integer example: 127 improvement_factor: type: number format: float example: 2.54 cloud_deployment_plan: type: object properties: primary_provider: type: string example: "AWS" fallback_providers: type: array items: type: string example: ["Azure", "GCP"] deployment_regions: type: array items: type: string example: ["us-east-1", "eu-west-1", "asia-pacific-1"] estimated_cost_monthly: type: number format: float example: 2847.50 execution_timeline: type: object properties: total_duration_minutes: type: integer example: 45 phases: type: array items: type: object properties: phase: type: string example: "autonomous_architecture" duration_minutes: type: integer example: 12 status: type: string enum: [completed, in_progress, pending] innovation_score: type: number format: float minimum: 0.0 maximum: 10.0 example: 9.6 legendary_agents_used: type: array items: type: string example: ["autonomous_architect", "proactive_quality", "evolutionary_prompts", "last_mile_cloud"] self_improvement_suggestions: type: array items: type: string example: ["Increase evolutionary prompt diversity", "Enhance cloud cost optimization", "Expand quality policy coverage"] future_evolution_path: type: object properties: next_capabilities: type: array items: type: string example: ["quantum computing integration", "autonomous feature development", "cross-dimensional scaling"] evolution_timeline_days: type: integer example: 30 AutonomousArchitectRequest: type: object required: - project_goals properties: project_goals: type: array items: type: string example: ["scalable microservices", "real-time processing", "AI-powered analytics"] description: High-level project goals and requirements constraints: type: array items: type: string example: ["budget under $5000/month", "latency under 100ms", "99.9% availability"] description: Technical and business constraints learning_objectives: type: array items: type: string example: ["optimize for performance", "learn user behavior patterns", "improve cost efficiency"] description: Areas where the architecture should learn and improve evolutionary_parameters: type: object properties: adaptation_rate: type: number format: float minimum: 0.1 maximum: 1.0 example: 0.7 innovation_tolerance: type: number format: float minimum: 0.0 maximum: 1.0 example: 0.8 AutonomousArchitectResponse: type: object properties: success: type: boolean example: true architecture_id: type: string example: "arch_revolutionary_001" dynamic_dag: type: object properties: nodes: type: array items: type: object properties: id: type: string example: "service_user_management" type: type: string example: "microservice" dependencies: type: array items: type: string optimization_score: type: number format: float example: 0.92 optimization_metrics: type: object properties: performance_efficiency: type: number format: float example: 0.94 cost_optimization: type: number format: float example: 0.87 maintainability: type: number format: float example: 0.91 evolutionary_features: type: array items: type: string example: ["adaptive load balancing", "autonomous scaling", "predictive resource allocation"] learning_plan: type: object properties: metrics_to_track: type: array items: type: string example: ["response_time", "throughput", "error_rate", "user_satisfaction"] improvement_cycle_days: type: integer example: 7 implementation_roadmap: type: array items: type: object properties: phase: type: string example: "core_services" estimated_duration_days: type: integer example: 14 deliverables: type: array items: type: string ProactiveQualityRequest: type: object required: - project_context properties: project_context: type: object properties: project_type: type: string example: "web_application" technology_stack: type: array items: type: string example: ["React", "Node.js", "PostgreSQL", "Docker"] team_size: type: integer example: 8 quality_objectives: type: array items: type: string example: ["security_excellence", "performance_optimization", "maintainability_focus"] policy_preferences: type: object properties: enforcement_strictness: type: string enum: [lenient, balanced, strict, revolutionary] default: revolutionary automation_level: type: string enum: [manual, semi_automated, fully_automated] default: fully_automated predictive_analysis: type: object properties: historical_data_available: type: boolean example: true risk_tolerance: type: string enum: [low, medium, high] example: low ProactiveQualityResponse: type: object properties: success: type: boolean example: true policy_framework_id: type: string example: "policy_revolutionary_001" quality_policies: type: array items: type: object properties: policy_id: type: string example: "security_scan_policy" name: type: string example: "Continuous Security Scanning" description: type: string example: "Automatically scan code for security vulnerabilities" enforcement_level: type: string enum: [warning, error, blocking] automation_enabled: type: boolean example: true predictive_indicators: type: array items: type: string example: ["code_complexity_increase", "dependency_vulnerabilities", "unusual_data_patterns"] predictive_insights: type: object properties: potential_issues: type: array items: type: object properties: issue_type: type: string example: "performance_degradation" probability: type: number format: float example: 0.73 predicted_timeline_days: type: integer example: 12 prevention_actions: type: array items: type: string example: ["optimize_database_queries", "implement_caching_layer"] continuous_improvement: type: object properties: learning_enabled: type: boolean example: true improvement_cycle_hours: type: integer example: 24 success_metrics: type: object properties: issue_prevention_rate: type: number format: float example: 0.89 quality_score_improvement: type: number format: float example: 0.15 EvolutionaryPromptRequest: type: object required: - base_prompt - optimization_goals properties: base_prompt: type: string description: Initial prompt to optimize and evolve example: "Generate a React component for user authentication" optimization_goals: type: array items: type: string example: ["accuracy", "creativity", "efficiency", "specificity"] description: Goals for prompt optimization evolution_parameters: type: object properties: population_size: type: integer minimum: 10 maximum: 100 example: 50 mutation_rate: type: number format: float minimum: 0.01 maximum: 0.5 example: 0.1 crossover_rate: type: number format: float minimum: 0.1 maximum: 0.9 example: 0.7 generations: type: integer minimum: 5 maximum: 100 example: 20 domain_context: type: string example: "web_development" description: Domain context for optimization performance_feedback: type: array items: type: object properties: prompt_variant: type: string performance_score: type: number format: float execution_time_ms: type: integer description: Historical performance feedback for learning EvolutionaryPromptResponse: type: object properties: success: type: boolean example: true optimization_id: type: string example: "evo_prompt_001" evolved_prompts: type: array items: type: object properties: generation: type: integer example: 15 prompt: type: string example: "Generate a comprehensive React authentication component with TypeScript, security best practices, and accessibility features" fitness_score: type: number format: float example: 0.94 genetic_markers: type: object properties: creativity_factor: type: number format: float example: 0.87 specificity_factor: type: number format: float example: 0.92 efficiency_factor: type: number format: float example: 0.85 evolution_statistics: type: object properties: total_generations: type: integer example: 20 improvement_factor: type: number format: float example: 2.34 convergence_generation: type: integer example: 16 diversity_score: type: number format: float example: 0.73 best_performing_prompt: type: object properties: prompt: type: string performance_metrics: type: object properties: accuracy: type: number format: float example: 0.96 creativity: type: number format: float example: 0.89 efficiency: type: number format: float example: 0.91 future_evolution_potential: type: object properties: mutation_suggestions: type: array items: type: string example: ["increase technical specificity", "add error handling context", "enhance accessibility requirements"] crossover_opportunities: type: array items: type: string example: ["combine with deployment prompts", "merge with testing specifications"] LastMileCloudRequest: type: object required: - application_package - deployment_requirements properties: application_package: type: object properties: source_type: type: string enum: [docker_image, source_code, artifact_bundle] example: docker_image location: type: string example: "my-registry/my-app:v1.0.0" build_requirements: type: object properties: runtime: type: string example: "node:18" dependencies: type: array items: type: string example: ["redis", "postgresql"] deployment_requirements: type: object properties: performance_targets: type: object properties: min_replicas: type: integer example: 2 max_replicas: type: integer example: 100 cpu_requests: type: string example: "100m" memory_requests: type: string example: "256Mi" target_response_time_ms: type: integer example: 200 availability_requirements: type: object properties: uptime_percentage: type: number format: float example: 99.9 disaster_recovery: type: boolean example: true compliance_requirements: type: array items: type: string example: ["GDPR", "SOC2", "HIPAA"] cloud_preferences: type: object properties: preferred_providers: type: array items: type: string example: ["AWS", "Azure"] cost_optimization: type: string enum: [minimum_cost, balanced, performance_optimized] example: balanced geographic_requirements: type: array items: type: string example: ["us-east", "eu-west", "asia-pacific"] autonomous_features: type: object properties: auto_scaling: type: boolean example: true auto_healing: type: boolean example: true cost_optimization: type: boolean example: true security_monitoring: type: boolean example: true LastMileCloudResponse: type: object properties: success: type: boolean example: true deployment_id: type: string example: "deploy_revolutionary_001" cloud_orchestration: type: object properties: primary_deployment: type: object properties: provider: type: string example: "AWS" region: type: string example: "us-east-1" cluster_id: type: string example: "eks-prod-cluster-001" endpoint: type: string example: "https://api.my-app.aws.example.com" failover_deployments: type: array items: type: object properties: provider: type: string example: "Azure" region: type: string example: "eastus" endpoint: type: string example: "https://api.my-app.azure.example.com" autonomous_verification: type: object properties: health_checks: type: array items: type: object properties: check_type: type: string example: "endpoint_availability" status: type: string enum: [passed, failed, warning] response_time_ms: type: integer example: 89 details: type: string performance_validation: type: object properties: load_test_results: type: object properties: requests_per_second: type: integer example: 5000 average_response_time_ms: type: integer example: 95 error_rate_percentage: type: number format: float example: 0.02 security_validation: type: object properties: vulnerability_scan_passed: type: boolean example: true ssl_certificate_valid: type: boolean example: true firewall_rules_applied: type: boolean example: true cost_optimization: type: object properties: estimated_monthly_cost: type: number format: float example: 1247.50 cost_optimization_recommendations: type: array items: type: string example: ["Use spot instances for non-critical workloads", "Enable auto-shutdown for development environments"] savings_achieved_percentage: type: number format: float example: 23.5 monitoring_setup: type: object properties: observability_dashboard: type: string example: "https://grafana.monitoring.example.com/dashboard/my-app" alerting_enabled: type: boolean example: true log_aggregation: type: string example: "centralized_elk_stack" autonomous_features_status: type: object properties: auto_scaling: type: object properties: enabled: type: boolean example: true current_replicas: type: integer example: 5 scaling_events_last_24h: type: integer example: 12 auto_healing: type: object properties: enabled: type: boolean example: true healing_events_last_24h: type: integer example: 2 continuous_optimization: type: object properties: enabled: type: boolean example: true optimization_cycle_hours: type: integer example: 6 # === CORE TOOL SCHEMAS === HealthResponse: type: object properties: status: type: string example: "revolutionary_healthy" service: type: string example: "multi-agent-orchestrator-legendary" version: type: string example: "3.0.0-LEGENDARY" revolutionary_features: type: object properties: legendary_agents_active: type: integer example: 4 autonomous_capabilities: type: boolean example: true evolutionary_intelligence: type: boolean example: true multi_cloud_orchestration: type: boolean example: true system_intelligence: type: object properties: ai_sophistication_level: type: string example: "revolutionary" self_improvement_active: type: boolean example: true predictive_capabilities: type: boolean example: true authentication: type: string example: "Descope OAuth 2.1 + PKCE + Non-Human Identity" analytics: type: string example: "Cequence AI Gateway + Legendary Metrics" mcp_protocol: type: string example: "2024-11-05 + Legendary Extensions" OrchestateTaskRequest: type: object required: - task_description - agent_preferences properties: task_description: type: string example: "Build a real-time chat application with AI moderation" agent_preferences: type: array items: type: string example: ["frontend", "backend", "devops"] complexity_level: type: string enum: [simple, medium, complex, legendary] default: complex include_legendary: type: boolean default: true description: Whether to include legendary agents in orchestration quality_requirements: type: object properties: security_level: type: string enum: [basic, high, revolutionary] default: high performance_targets: type: object properties: response_time_ms: type: integer example: 100 OrchestateTaskResponse: type: object properties: success: type: boolean example: true orchestration_id: type: string example: "orch_legendary_001" agents_involved: type: array items: type: string example: ["frontend", "backend", "devops", "autonomous_architect", "proactive_quality"] execution_plan: type: array items: type: object properties: step: type: integer agent: type: string task: type: string estimated_duration_minutes: type: integer revolutionary_enhancements: type: array items: type: string example: ["autonomous architecture optimization", "predictive quality assurance", "evolutionary prompt enhancement"] # === STANDARD MCP PROTOCOL SCHEMAS === MCPInitializeRequest: type: object properties: jsonrpc: type: string example: "2.0" id: type: string example: "1" method: type: string example: "initialize" params: type: object properties: protocolVersion: type: string example: "2024-11-05" capabilities: type: object properties: experimental: type: object properties: legendary_agents: type: boolean example: true clientInfo: type: object properties: name: type: string example: "Claude Desktop" version: type: string example: "1.0.0" MCPInitializeResponse: type: object properties: jsonrpc: type: string example: "2.0" id: type: string example: "1" result: type: object properties: protocolVersion: type: string example: "2024-11-05" capabilities: type: object properties: experimental: type: object properties: legendary_agents: type: boolean example: true tools: type: object properties: listChanged: type: boolean example: true legendary_enabled: type: boolean example: true serverInfo: type: object properties: name: type: string example: "multi-agent-orchestrator-legendary" version: type: string example: "3.0.0-LEGENDARY" description: type: string example: "Revolutionary MCP server with 4 legendary AI agents and autonomous capabilities" MCPListRequest: type: object properties: jsonrpc: type: string example: "2.0" id: type: string example: "2" method: type: string example: "tools/list" MCPToolsListResponse: type: object properties: jsonrpc: type: string example: "2.0" id: type: string example: "2" result: type: object properties: tools: type: array items: type: object properties: name: type: string example: "legendary_generate_application" description: type: string example: "Revolutionary application generation using all 4 legendary agents" category: type: string example: "legendary" inputSchema: type: object MCPToolCallRequest: type: object properties: jsonrpc: type: string example: "2.0" id: type: string example: "3" method: type: string example: "tools/call" params: type: object properties: name: type: string example: "legendary_generate_application" arguments: type: object MCPToolCallResponse: type: object properties: jsonrpc: type: string example: "2.0" id: type: string example: "3" result: type: object properties: content: type: array items: type: object properties: type: type: string example: "text" text: type: string # === ADDITIONAL CORE SCHEMAS === PingRequest: type: object properties: message: type: string example: "Revolutionary ping test" include_legendary_status: type: boolean default: true PingResponse: type: object properties: status: type: string example: "revolutionary_pong" timestamp: type: string format: date-time message: type: string example: "Revolutionary ping test" legendary_status: type: object properties: agents_active: type: integer example: 4 capabilities_enabled: type: array items: type: string example: ["autonomous_architecture", "proactive_quality", "evolutionary_prompts", "cloud_orchestration"] server_info: type: object properties: python_version: type: string example: "3.11.5" platform: type: string example: "Linux-5.4.0-x86_64" revolutionary_features: type: boolean example: true SystemStatusRequest: type: object properties: include_legendary: type: boolean default: true include_metrics: type: boolean default: true SystemStatusResponse: type: object properties: status: type: string example: "revolutionary_healthy" timestamp: type: string format: date-time server: type: string example: "healthy" orchestrator: type: object properties: status: type: string example: "active" agents_available: type: array items: type: string example: ["frontend", "backend", "devops", "reviewer"] legendary_agents: type: object properties: autonomous_architect: type: object properties: status: type: string example: "ready" active_architectures: type: integer example: 3 proactive_quality: type: object properties: status: type: string example: "monitoring" policies_active: type: integer example: 15 evolutionary_prompts: type: object properties: status: type: string example: "evolving" generations_completed: type: integer example: 127 last_mile_cloud: type: object properties: status: type: string example: "orchestrating" active_deployments: type: integer example: 8 revolutionary_capabilities: type: boolean example: true authentication: type: string example: "enabled" analytics: type: string example: "enabled" healing_enabled: type: boolean example: true CapabilitiesResponse: type: object properties: core_capabilities: type: array items: type: string example: ["multi_agent_orchestration", "autonomous_healing", "code_generation"] legendary_capabilities: type: array items: type: string example: ["autonomous_architecture", "proactive_quality", "evolutionary_prompts", "cloud_orchestration"] ai_sophistication: type: string example: "revolutionary" self_improvement: type: boolean example: true total_tools: type: integer example: 12 legendary_tools: type: integer example: 5 GenerateArchitectureRequest: type: object required: - requirements properties: requirements: type: string example: "Scalable e-commerce platform with microservices" complexity: type: string enum: [simple, medium, complex, enterprise] default: medium preferences: type: object properties: cloud_provider: type: string example: "AWS" architecture_style: type: string example: "microservices" GenerateArchitectureResponse: type: object properties: success: type: boolean example: true architecture: type: object properties: components: type: array items: type: object properties: name: type: string type: type: string description: type: string data_flow: type: object deployment_strategy: type: object AutoFixCodeRequest: type: object required: - code - error_message properties: code: type: string example: "def calculate_total(items):\\n return sum(item.price for item in items)" error_message: type: string example: "AttributeError: 'dict' object has no attribute 'price'" context: type: string example: "E-commerce cart calculation" AutoFixCodeResponse: type: object properties: success: type: boolean example: true fixed_code: type: string example: "def calculate_total(items):\\n return sum(item['price'] for item in items)" explanation: type: string example: "Changed item.price to item['price'] to handle dict objects" confidence: type: number format: float example: 0.95 changes_made: type: array items: type: string example: ["Changed attribute access to dictionary key access"] tags: - name: 🌟 Legendary Tools description: Revolutionary AI agents with autonomous and evolutionary capabilities - name: Core Agent Tools description: Multi-agent orchestration and core capabilities - name: MCP Protocol description: Model Context Protocol implementation with legendary extensions - name: MCP Tools description: Tool management and execution with legendary support - name: Infrastructure description: System monitoring and infrastructure management - name: Health & Status description: Health monitoring and status reporting - name: Analytics & Monitoring description: Advanced analytics with Cequence AI Gateway integration