Multi-Agent MCP Network

A production-ready Model Context Protocol (MCP) server that exposes multiple specialized AI agents through a unified interface. Each agent is an expert in its domain and they collaborate through an intelligent orchestrator.

Architecture

                    ┌─────────────────────┐
                    │   Client / MCP Host  │
                    └──────────┬──────────┘
                               │
                    ┌──────────▼──────────┐
                    │  REST API (Express)  │
                    │  MCP Server (SDK)   │
                    └──────────┬──────────┘
                               │
                    ┌──────────▼──────────┐
                    │    Orchestrator     │
                    │  ┌─────┴─────┐     │
                    │  │ Router    │     │
                    │  │ Workflow  │     │
                    │  └─────┬─────┘     │
                    └──────────┬──────────┘
                               │
          ┌────────────────────┼────────────────────┐
          ▼        ▼           ▼          ▼         ▼
       ┌────┐  ┌────┐     ┌────┐     ┌────┐    ┌────┐
       │CEO │  │CTO │ ... │Mktg│     │ QA │    │ ...│
       └────┘  └────┘     └────┘     └────┘    └────┘
          │        │          │          │
          └────────┴──────────┴──────────┘
                               │
                    ┌──────────▼──────────┐
                    │  Memory Layer       │
                    │  PostgreSQL + Qdrant│
                    └─────────────────────┘

Agents

Agent	Role	Expertise
CEO	Business Strategy	Market analysis, product roadmap, pricing, investment, startup advice
CTO	Technology	Software architecture, backend, frontend, databases, AI/ML, DevOps, cloud
Designer	Design	UI/UX, brand identity, logos, color palettes, design systems
Sales	Revenue	Lead generation, cold emails, CRM, sales funnels, outreach
Marketing	Growth	SEO, content, ads, social media, email campaigns, competitor analysis
QA	Quality	Code review, bug finding, testing, security, performance

Tech Stack

• Runtime: Node.js 20+, TypeScript
• Framework: Express, FastMCP SDK (@modelcontextprotocol/sdk)
• Databases: PostgreSQL (pgvector), Qdrant (vector), Redis (cache)
• AI: OpenAI, Anthropic Claude, Google Gemini
• Infrastructure: Docker, Docker Compose

Quick Start

Prerequisites

• Node.js 20+
• Docker & Docker Compose
• At least one AI provider API key (OpenAI, Anthropic, or Gemini)

1. Clone & Install

cd multi-agent-mcp
npm install

2. Configure Environment

cp .env.example .env

Edit .env and add your API keys:

OPENAI_API_KEY=sk-...
ANTHROPIC_API_KEY=sk-ant-...
GEMINI_API_KEY=...
API_KEY=sk-mcp-your-secret-key
JWT_SECRET=your-random-secret

3. Start Infrastructure

docker compose up -d postgres qdrant redis

4. Run Database Migrations

npm run db:migrate

5. Start the Server

Development mode:

npm run dev

Production mode:

npm run build
npm start

6. Start MCP Server (for MCP clients)

npm run mcp

API Endpoints

All endpoints require x-api-key header matching your API_KEY env var.

Method	Endpoint	Description
POST	/chat	Send query to orchestrator (auto-routes to agents)
POST	/agent/ceo	Ask CEO directly
POST	/agent/cto	Ask CTO directly
POST	/agent/designer	Ask Designer directly
POST	/agent/sales	Ask Sales directly
POST	/agent/marketing	Ask Marketing directly
POST	/agent/qa	Ask QA directly
POST	/memory	Save or search memory
GET	/projects	List all projects
GET	/projects/:id	Get project details
GET	/tasks	List tasks
GET	/health	Health check

Chat Example

curl -X POST http://localhost:3001/chat \
  -H "Content-Type: application/json" \
  -H "x-api-key: sk-mcp-your-secret-key" \
  -d '{"query": "I want to launch an AI SaaS for small businesses"}'

MCP Tools

When running as an MCP server (via npm run mcp), the following tools are exposed:

Tool	Description
ask_ceo	Business strategy advice
ask_cto	Technical architecture guidance
ask_designer	UI/UX and brand design
ask_sales	Sales and lead generation
ask_marketing	Marketing and growth
ask_qa	Code review and quality
ask_all_agents	Multi-agent collaboration
create_project	Create a new project
save_memory	Store long-term memory
load_memory	Retrieve memories
search_documents	Semantic document search
generate_strategy	Business strategy generation
generate_ui	UI design generation
generate_architecture	System architecture design
generate_marketing_plan	Marketing plan generation
generate_sales_plan	Sales plan generation
review_project	Full project review

Docker Deployment

Start everything with one command:

docker compose up --build

This starts:

• app - The Multi-Agent MCP server
• postgres - PostgreSQL with pgvector
• qdrant - Vector database for embeddings
• redis - Cache layer

Environment Variables

Variable	Required	Description
API_KEY	Yes	API authentication key
JWT_SECRET	Yes	JWT signing secret
OPENAI_API_KEY	No*	OpenAI API key
ANTHROPIC_API_KEY	No*	Anthropic API key
GEMINI_API_KEY	No*	Google Gemini API key
DATABASE_URL	No	PostgreSQL connection string
QDRANT_URL	No	Qdrant endpoint
REDIS_URL	No	Redis connection string

*At least one AI provider API key is required.

Project Structure

src/
├── agents/          # Agent implementations
│   ├── BaseAgent.ts # Abstract base class
│   ├── CEOAgent.ts
│   ├── CTOAgent.ts
│   ├── DesignerAgent.ts
│   ├── SalesAgent.ts
│   ├── MarketingAgent.ts
│   └── QAAgent.ts
├── orchestrator/    # Routing & workflow
│   ├── Router.ts    # Intent detection, agent selection
│   └── Workflow.ts  # Multi-agent execution, response merging
├── memory/          # Persistence layer
│   ├── postgres.ts  # PostgreSQL client
│   ├── qdrant.ts    # Qdrant vector client
│   ├── logger.ts    # Winston logger
│   └── migrate.ts   # DB migration runner
├── tools/           # MCP server
│   └── server.ts    # FastMCP SDK server with tool registration
├── config/          # Configuration
│   └── index.ts     # Env var loading
├── types/           # TypeScript types
│   └── index.ts     # All type definitions
└── index.ts         # Express REST API entry point

Adding a New Agent

1. Create src/agents/YourAgent.ts extending BaseAgent
2. Add your agent role to AgentRole enum in src/types/index.ts
3. Add a system prompt in SYSTEM_PROMPTS in src/types/index.ts
4. Register the agent in Router.ts constructor
5. Add MCP tool in src/tools/server.ts
6. Add REST endpoint in src/index.ts
7. Add SQL seed in sql/schema.sql

License

MIT