Supports containerized deployment of the orchestrator server with environment configuration.
Built on FastAPI framework for HTTP transport and MCP server implementation.
Required for cloning and managing the orchestrator repository locally.
Planned integration for CI/CD automation and development workflow management.
Planned integration for project management and issue tracking in development workflows.
Uses OpenAI SDK for AI-powered agent capabilities in architecture generation, code fixing, and application development.
Core runtime environment (3.11+) for the multi-agent orchestrator server.
Planned integration for real-time collaboration and incident notifications in distributed development teams.
Multi Agent Orchestrator MCP
An enterprise‑grade Model Context Protocol (MCP) server for autonomous software engineering. It coordinates specialized agents (Architecture, Quality, Cloud, Prompt) to plan, build, test, and deploy applications with self‑healing, authentication, and analytics.
Check out!
Smithery Platfrom Deployed Link: https://smithery.ai/server/@yoriichi-07/multi_orchestrator_mcp
Team
Team Name : UpsideDown
Member : Shreesaanth R
Hackathon
Theme 2: Build a Secure MCP Server for Agents (w/ Cequence)
Challenge addressed: Build a production‑ready MCP server that orchestrates multiple agents with authentication (Descope), hosting (Cequence), and self‑healing to reliably execute end‑to‑end development workflows, deployable on Smithery.
Requirements
Python 3.11+
Git
An MCP‑compatible client (VS Code, Cursor, Windsurf, Claude Desktop, etc.)
Getting started
First, install the server with your MCP client. For an overview of client support and mechanics, see the official MCP quickstart: https://modelcontextprotocol.io/quickstart/user
Standard config (works in most clients)
One Click installation
Follow the MCP install guide: https://code.visualstudio.com/docs/copilot/chat/mcp-servers#_add-an-mcp-server
Or via CLI:
Click the button to install (if the deeplink is not supported on your OS, use the manual steps below):
Manual: Go to Cursor Settings → MCP → Add new MCP Server. Choose command type and set:
Use the CLI then paste the standard config above:
Follow the MCP quickstart: https://modelcontextprotocol.io/quickstart/user. Use the standard config above.
Use the Install → Edit mcp.json, paste the standard config. One-click:
Docs: https://docs.windsurf.com/windsurf/cascade/mcp. Use the standard config above (replace URL with http://localhost:8080 for local).
Configuration
Environment variables (see config/env.template):
DESCOPE_PROJECT_ID,DESCOPE_MANAGEMENT_KEY,DESCOPE_ACCESS_KEY– enable Descope authentication (optional for local/dev).PORT– server port (default8080).DESCOPE_DEMO_MODE– settruefor local testing without full auth.CEQUENCE_GATEWAY_ID,CEQUENCE_API_KEY– enable Cequence analytics (optional).JWT_SECRET_KEY,CORS_ORIGINS,RATE_LIMIT_REQUESTS, logging toggles.
Client configuration templates are provided in config/mcp.json.template (direct JWT or auto‑refresh proxy modes).
Capabilities
orchestrate_task
Title: Orchestrate multi‑agent task
Description: Coordinate Frontend/Backend/DevOps/QA agents for development, testing, or deployment.
Parameters:
task_description(string),task_type(enum: development|architecture|testing|deployment),priority(enum)
generate_architecture
Title: Generate architecture
Description: Produce system architecture with components and recommendations.
Parameters:
project_description(string),tech_stack(string[]),requirements(string[])
auto_fix_code
Title: Self‑healing fix
Description: Generate fixes for code using error context and explanations.
Parameters:
code(string),error_message(string),context(string)
list_capabilities
Title: Catalog
Description: Summarize available agents, tools, enterprise features, and supported tasks.
Parameters: none
get_system_status
Title: System status
Description: Returns server health, agent availability, analytics/auth status, and timestamp.
Parameters: none
advanced_generate_application
Title: Enterprise app generation
Description: Plan and generate an application using advanced agents and deployment strategies.
Parameters:
description(string),complexity_level(enum),innovation_requirements(string[]),deployment_strategy(enum)
autonomous_architect
Title: Autonomous architect
Description: Builds an execution DAG and adaptive strategy from goals and constraints.
Parameters:
project_goals(string[]),constraints(string[]),learning_objectives(string[])
proactive_quality_assurance
Title: Proactive quality
Description: Applies policy‑as‑code checks with optional auto‑remediation.
Parameters:
code_context(string),quality_standards(string[]),auto_remediation(bool)
evolutionary_prompt_optimization
Title: Prompt evolution
Description: Creates and evolves prompts based on goals and performance metrics.
Parameters:
base_prompt(string),optimization_goals(string[]),performance_metrics(object)
last_mile_cloud_deployment
Title: Cloud deployment
Description: Plans deployment, verifies environments, and returns rollback/monitoring setup.
Parameters:
application_context(string),target_environments(string[]),verification_requirements(string[])
ping
Title: Health check
Description: Simple liveness probe.
Parameters: none
debug_server_config
Title: Debug configuration (temporary)
Description: Exposes non‑secret configuration metadata for diagnostics.
Parameters: none
mcp://capabilities— capabilities and catalog (JSON)mcp://analytics— analytics snapshot (requires Cequence)mcp://health— system health snapshot
project-setup— guided setup plancode-review— structured review outlinerevolutionary-development— advanced strategy plan using autonomous agents
Tech stack
Full dependencies are declared in requirements.txt and pyproject.toml.
Demo video
Link: (coming soon)
Future Roadmap
Enhanced Agent Intelligence
Implement reinforcement learning for agent coordination optimization
Add context‑aware agents that learn from project history and patterns
Develop specialized agents for mobile, ML, and blockchain development
Advanced Automation
Build predictive analytics to forecast development challenges
Create automated testing strategies with comprehensive edge case generation
Implement intelligent resource optimization for cloud deployments
Enterprise Features
Add multi‑tenant architecture with organization‑specific agent training
Implement advanced compliance standards (SOC2, HIPAA, PCI‑DSS)
Create custom agent marketplace for domain‑specific development patterns
Developer Experience
Build a visual development interface for non‑technical users
Integrate with Jira, GitHub Actions, Slack, and incident tooling
Enable real‑time collaboration for distributed development teams
This server cannot be installed