Price Per TokenPrice Per Token
Multi Orchestrator

Multi Orchestrator

by yoriichi-07

GitHub 1 346 uses Remote
0

About

Multi Orchestrator is an enterprise-grade MCP server that coordinates specialized AI agents to automate complete software engineering workflows from architecture design through deployment. Key capabilities include: - Four specialized agent roles: Architecture, Quality, Cloud, and Prompt agents that collaborate on complex development tasks - End-to-end automation covering system planning, code generation, comprehensive testing, and production deployment - Self-healing mechanisms that automatically detect and remediate code issues, infrastructure failures, and execution errors - Enterprise-grade authentication via Descope and secure hosting support via Cequence for production environments - Real-time health monitoring and analytics dashboard to track project velocity, system performance, and development metrics - Compatible with VS Code, Cursor, Windsurf, and Claude Desktop through Smithery deployment platform

README

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)

    {
      "mcpServers": {
        "multi_orchestrator_mcp": {
          "command": "cmd",
          "args": [
            "/c",
            "npx",
            "-y",
            "@smithery/cli@latest",
            "run",
            "@yoriichi-07/multi_orchestrator_mcp",
            "--key",
            "70fd8cf1-9dd3-4556-8a43-78916f617fb2"
          ]
        }
      }
    }
    

    VS Code

  • One Click installation
  • [](https://vscode.dev/redirect?url=vscode%3Amcp%2Finstall%3F%257B%2522name%2522%253A%2522multi_orchestrator_mcp%2522%252C%2522command%2522%253A%2522npx%2522%252C%2522args%2522%253A%255B%2522-y%2522%252C%2522%2540smithery%2Fcli%2540latest%2522%252C%2522run%2522%252C%2522%2540yoriichi-07%252Fmulti_orchestrator_mcp%2522%252C%2522--key%2522%252C%252270fd8cf1-9dd3-4556-8a43-78916f617fb2%2522%255D%257D) [](https://insiders.vscode.dev/redirect?url=vscode-insiders%3Amcp%2Finstall%3F%257B%2522name%2522%253A%2522multi_orchestrator_mcp%2522%252C%2522command%2522%253A%2522npx%2522%252C%2522args%2522%253A%255B%2522-y%2522%252C%2522%2540smithery%2Fcli%2540latest%2522%252C%2522run%2522%252C%2522%2540yoriichi-07%252Fmulti_orchestrator_mcp%2522%252C%2522--key%2522%252C%252270fd8cf1-9dd3-4556-8a43-78916f617fb2%2522%255D%257D)

  • Follow the MCP install guide: https://code.visualstudio.com/docs/copilot/chat/mcp-servers#_add-an-mcp-server
  • Or via CLI:
  • # VS Code (stable)
    npx -y @smithery/cli@latest install @yoriichi-07/multi_orchestrator_mcp --client vscode --key 70fd8cf1-9dd3-4556-8a43-78916f617fb2

    VS Code Insiders

    npx -y @smithery/cli@latest install @yoriichi-07/multi_orchestrator_mcp --client vscode-insiders --key 70fd8cf1-9dd3-4556-8a43-78916f617fb2

    Cursor

    Click the button to install (if the deeplink is not supported on your OS, use the manual steps below):

    [](cursor://anysphere.cursor-deeplink/mcp/install?name=Multi%20Orchestrator&config=eyJjb21tYW5kIjoibnB4IiwiYXJncyI6WyIteSIsIkBzbWl0aGVyeS9jbGlAbGF0ZXN0IiwicnVuIiwiQHlvcmlpY2hpLTA3L211bHRpX29yY2hlc3RyYXRvcl9tY3AiLCItLWtleSIsIjcwZmQ4Y2YxLTlkZDMtNDU1Ni04YTQzLTc4OTE2ZjYxN2ZiMiJdfQ==)

    Manual: Go to Cursor SettingsMCPAdd new MCP Server. Choose command type and set:

    npx -y @smithery/cli@latest install @yoriichi-07/multi_orchestrator_mcp --client cursor --key 70fd8cf1-9dd3-4556-8a43-78916f617fb2
    

    Claude Code

    Use the CLI then paste the standard config above:

    claude mcp add --transport http yoriichi-07-multi-orchestrator-mcp "https://server.smithery.ai/@yoriichi-07/multi_orchestrator_mcp/mcp"
    

    Claude Desktop

    Follow the MCP quickstart: https://modelcontextprotocol.io/quickstart/user. Use the standard config above.

    LM Studio

    Use the Install → Edit mcp.json, paste the standard config. One-click: [](https://lmstudio.ai/install-mcp?name=multi-orchestrator&config=eyJjb21tYW5kIjoibnB4IiwiYXJncyI6WyIteSIsIkBtb2RlbGNvbnRleHRwcm90b2NvbC9zZXJ2ZXItZmV0Y2giLCJodHRwczovL3NtaXRoZXJ5LmFpL3NlcnZlci9AeW9yaWljaGktMDcvbXVsdGlfb3JjaGVzdHJhdG9yX21jcCJdfQ==)

    Windsurf

    Docs: https://docs.windsurf.com/windsurf/cascade/mcp. Use the standard config above (replace URL with http://localhost:8080 for local).

    Run locally

    ```bash

    Clone and install

    Related MCP Servers

    AI Research Assistant

    AI Research Assistant

    hamid-vakilzadeh

    AI Research Assistant provides comprehensive access to millions of academic papers through the Semantic Scholar and arXiv databases. This MCP server enables AI coding assistants to perform intelligent literature searches, citation network analysis, and paper content extraction without requiring an API key. Key features include: - Advanced paper search with multi-filter support by year ranges, citation thresholds, field of study, and publication type - Title matching with confidence scoring for finding specific papers - Batch operations supporting up to 500 papers per request - Citation analysis and network exploration for understanding research relationships - Full-text PDF extraction from arXiv and Wiley open-access content (Wiley TDM token required for institutional access) - Rate limits of 100 requests per 5 minutes with options to request higher limits through Semantic Scholar

    Web & Search
    12 8
    Linkup

    Linkup

    LinkupPlatform

    Linkup is a real-time web search and content extraction service that enables AI assistants to search the web and retrieve information from trusted sources. It provides source-backed answers with citations, making it ideal for fact-checking, news gathering, and research tasks. Key features of Linkup: - Real-time web search using natural language queries to find current information, news, and data - Page fetching to extract and read content from any webpage URL - Search depth modes: Standard for direct-answer queries and Deep for complex research across multiple sources - Source-backed results with citations and context from relevant, trustworthy websites - JavaScript rendering support for accessing dynamic content on JavaScript-heavy pages

    Web & Search
    2 24

    context7

    huynguyen03dev

    5