---
title: 'Installation Guide'
description: 'Detailed installation instructions for all platforms'
---

## Prerequisites

Before installing MCPHub, ensure you have the following prerequisites:

- **Node.js** 18+ (for local development)
- **Docker** (recommended for production)
- **pnpm** (for local development)

Optional for Smart Routing:

- **PostgreSQL** with pgvector extension
- **OpenAI API Key** or compatible embedding service

## Installation Methods

<Tabs>
  <Tab title="Docker (Recommended)">
    ### Docker Installation

    Docker is the recommended way to deploy MCPHub in production.

    #### 1. Basic Installation

    ```bash
    # Pull the latest image
    docker pull samanhappy/mcphub:latest

    # Run with default settings
    docker run -d \
      --name mcphub \
      -p 3000:3000 \
      samanhappy/mcphub:latest
    ```

    #### 2. With Custom Configuration

    ```bash
    # Create your configuration file
    cat > mcp_settings.json << 'EOF'
    {
      "mcpServers": {
        "fetch": {
          "command": "uvx",
          "args": ["mcp-server-fetch"]
        },
        "playwright": {
          "command": "npx",
          "args": ["@playwright/mcp@latest", "--headless"]
        }
      }
    }
    EOF

    # Run with mounted config
    docker run -d \
      --name mcphub \
      -p 3000:3000 \
      -v $(pwd)/mcp_settings.json:/app/mcp_settings.json \
      samanhappy/mcphub:latest
    ```

    #### 3. With Environment Variables

    ```bash
    docker run -d \
      --name mcphub \
      -p 3000:3000 \
      -e PORT=3000 \
      -e BASE_PATH="" \
      samanhappy/mcphub:latest
    ```

    #### 4. Docker Compose

    Create a `docker-compose.yml` file:

    ```yaml
    version: '3.8'
    services:
      mcphub:
        image: samanhappy/mcphub:latest
        ports:
          - "3000:3000"
        volumes:
          - ./mcp_settings.json:/app/mcp_settings.json
        environment:
          - PORT=3000
          - BASE_PATH=""
          - REQUEST_TIMEOUT=60000
        restart: unless-stopped

      # Optional: PostgreSQL for Smart Routing
      postgres:
        image: pgvector/pgvector:pg16
        environment:
          POSTGRES_DB: mcphub
          POSTGRES_USER: mcphub
          POSTGRES_PASSWORD: mcphub_password
        volumes:
          - postgres_data:/var/lib/postgresql/data
        ports:
          - "5432:5432"

    volumes:
      postgres_data:
    ```

    Run with:
    ```bash
    docker-compose up -d
    ```

  </Tab>

  <Tab title="npm Package">
    ### npm Package Installation

    Install MCPHub as a global npm package:

    #### 1. Global Installation

    ```bash
    # Install globally
    npm install -g @samanhappy/mcphub

    # Or with yarn
    yarn global add @samanhappy/mcphub

    # Or with pnpm
    pnpm add -g @samanhappy/mcphub
    ```

    #### 2. Running MCPHub

    ```bash
    # Run with default settings
    mcphub

    # Run with custom port
    PORT=8080 mcphub
    ```

    {/* #### 3. Local Installation

    You can also install MCPHub locally in a project:

    ```bash
    # Create a new directory
    mkdir my-mcphub
    cd my-mcphub

    # Initialize package.json
    npm init -y

    # Install MCPHub locally
    npm install @samanhappy/mcphub

    # Create a start script
    echo '#!/bin/bash\nnpx mcphub' > start.sh
    chmod +x start.sh

    # Run MCPHub
    ./start.sh
    ``` */}
  </Tab>

  <Tab title="Local Development">
    ### Local Development Setup

    For development, customization, or contribution:

    #### 1. Clone Repository

    ```bash
    # Clone the repository
    git clone https://github.com/samanhappy/mcphub.git
    cd mcphub
    ```

    #### 2. Install Dependencies

    ```bash
    # Install dependencies with pnpm (recommended)
    pnpm install

    # Or with npm
    npm install

    # Or with yarn
    yarn install
    ```

    #### 3. Development Mode

    ```bash
    # Start both backend and frontend in development mode
    pnpm dev

    # This will start:
    # - Backend on http://localhost:3001
    # - Frontend on http://localhost:5173
    # - Frontend proxies API calls to backend
    ```

    #### 4. Build for Production

    ```bash
    # Build both backend and frontend
    pnpm build

    # Start production server
    pnpm start
    ```

    #### 5. Development Scripts

    ```bash
    # Backend only (for API development)
    pnpm backend:dev

    # Frontend only (when backend is running separately)
    pnpm frontend:dev

    # Run tests
    pnpm test

    # Lint code
    pnpm lint

    # Format code
    pnpm format
    ```

    <Note>
      On Windows, you may need to run backend and frontend separately:
      ```bash
      # Terminal 1: Backend
      pnpm backend:dev

      # Terminal 2: Frontend
      pnpm frontend:dev
      ```
    </Note>

  </Tab>

  <Tab title="Kubernetes">
    ### Kubernetes Deployment

    Deploy MCPHub on Kubernetes with these manifests:

    #### 1. ConfigMap for Settings

    ```yaml
    apiVersion: v1
    kind: ConfigMap
    metadata:
      name: mcphub-config
    data:
      mcp_settings.json: |
        {
          "mcpServers": {
            "fetch": {
              "command": "uvx",
              "args": ["mcp-server-fetch"]
            },
            "playwright": {
              "command": "npx",
              "args": ["@playwright/mcp@latest", "--headless"]
            }
          }
        }
    ```

    #### 2. Deployment

    ```yaml
    apiVersion: apps/v1
    kind: Deployment
    metadata:
      name: mcphub
    spec:
      replicas: 1
      selector:
        matchLabels:
          app: mcphub
      template:
        metadata:
          labels:
            app: mcphub
        spec:
          containers:
          - name: mcphub
            image: samanhappy/mcphub:latest
            ports:
            - containerPort: 3000
            env:
            - name: PORT
              value: "3000"
            volumeMounts:
            - name: config
              mountPath: /app/mcp_settings.json
              subPath: mcp_settings.json
          volumes:
          - name: config
            configMap:
              name: mcphub-config
    ```

    #### 3. Service

    ```yaml
    apiVersion: v1
    kind: Service
    metadata:
      name: mcphub-service
    spec:
      selector:
        app: mcphub
      ports:
      - port: 80
        targetPort: 3000
      type: ClusterIP
    ```

    #### 4. Ingress (Optional)

    ```yaml
    apiVersion: networking.k8s.io/v1
    kind: Ingress
    metadata:
      name: mcphub-ingress
      annotations:
        nginx.ingress.kubernetes.io/proxy-buffering: "off"
    spec:
      rules:
      - host: mcphub.yourdomain.com
        http:
          paths:
          - path: /
            pathType: Prefix
            backend:
              service:
                name: mcphub-service
                port:
                  number: 80
    ```

    Deploy with:
    ```bash
    kubectl apply -f mcphub-configmap.yaml
    kubectl apply -f mcphub-deployment.yaml
    kubectl apply -f mcphub-service.yaml
    kubectl apply -f mcphub-ingress.yaml
    ```

  </Tab>
</Tabs>

## Smart Routing Setup (Optional)

Smart Routing provides AI-powered tool discovery using vector semantic search.

### Prerequisites

1. **PostgreSQL with pgvector**
2. **OpenAI API Key** (or compatible embedding service)

### Database Setup

<Tabs>
  <Tab title="Docker PostgreSQL">
    ```bash
    # Run PostgreSQL with pgvector
    docker run -d \
      --name mcphub-postgres \
      -e POSTGRES_DB=mcphub \
      -e POSTGRES_USER=mcphub \
      -e POSTGRES_PASSWORD=your_password \
      -p 5432:5432 \
      pgvector/pgvector:pg16
    ```
  </Tab>

  <Tab title="Existing PostgreSQL">
    If you have an existing PostgreSQL instance:

    ```sql
    -- Connect to your PostgreSQL instance
    -- Create database
    CREATE DATABASE mcphub;

    -- Connect to the mcphub database
    \c mcphub;

    -- Enable pgvector extension
    CREATE EXTENSION IF NOT EXISTS vector;
    ```

  </Tab>

  <Tab title="Cloud PostgreSQL">
    For cloud providers (AWS RDS, Google Cloud SQL, etc.):

    1. Enable the pgvector extension in your cloud provider's console
    2. Create a database named `mcphub`
    3. Note down the connection details

  </Tab>
</Tabs>

{/* ### Environment Configuration

Set the following environment variables:

```bash
# Database connection
DATABASE_URL=postgresql://mcphub:your_password@localhost:5432/mcphub

# OpenAI API for embeddings
OPENAI_API_KEY=your_openai_api_key

# Optional: Custom embedding model
EMBEDDING_MODEL=text-embedding-3-small

# Optional: Enable smart routing
ENABLE_SMART_ROUTING=true
``` */}

## Verification

After installation, verify MCPHub is working:

{/* ### 1. Health Check

```bash
curl http://localhost:3000/api/health
```

Expected response:

```json
{
  "status": "ok",
  "version": "x.x.x",
  "uptime": 123
}
``` */}

### Dashboard Access

Open your browser and navigate to:

```
http://localhost:3000
```

{/* ### 3. API Test

```bash
curl -X POST http://localhost:3000/mcp \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0",
    "id": 1,
    "method": "tools/list",
    "params": {}
  }'
``` */}

## Troubleshooting

<AccordionGroup>
  <Accordion title="Docker Issues">
    **Port already in use:**
    ```bash
    # Check what's using port 3000
    lsof -i :3000

    # Use a different port
    docker run -p 8080:3000 samanhappy/mcphub
    ```

    **Container won't start:**
    ```bash
    # Check container logs
    docker logs mcphub

    # Run interactively for debugging
    docker run -it --rm samanhappy/mcphub /bin/bash
    ```

  </Accordion>

  <Accordion title="npm Installation Issues">
    **Permission errors:**
    ```bash
    # Use npx instead of global install
    npx @samanhappy/mcphub

    # Or fix npm permissions
    npm config set prefix ~/.npm-global
    export PATH=~/.npm-global/bin:$PATH
    ```

    **Node version issues:**
    ```bash
    # Check Node version
    node --version

    # Install Node 18+ using nvm
    nvm install 18
    nvm use 18
    ```

  </Accordion>

  <Accordion title="Network Issues">
    **Can't access dashboard:**
    - Check if MCPHub is running: `ps aux | grep mcphub`
    - Verify port binding: `netstat -tlnp | grep 3000`
    - Check firewall settings
    - Try accessing via `127.0.0.1:3000` instead of `localhost:3000`

    **AI clients can't connect:**
    - Ensure the endpoint URL is correct
    - Check if MCPHub is behind a proxy
    - Verify network policies in Kubernetes/Docker environments

  </Accordion>

  <Accordion title="Smart Routing Issues">
    **Database connection failed:**
    ```bash
    # Test database connection
    psql $DATABASE_URL -c "SELECT 1;"

    # Check if pgvector is installed
    psql $DATABASE_URL -c "CREATE EXTENSION IF NOT EXISTS vector;"
    ```

    **Embedding service errors:**
    - Verify OpenAI API key is valid
    - Check internet connectivity
    - Monitor rate limits

  </Accordion>
</AccordionGroup>

## Next Steps

<CardGroup cols={2}>
  <Card title="Configuration" icon="cog" href="/configuration/mcp-settings">
    Configure your MCP servers and settings
  </Card>
  <Card title="Quick Start" icon="rocket" href="/quickstart">
    Get up and running in 5 minutes
  </Card>
  <Card title="Server Management" icon="server" href="/features/server-management">
    Learn how to manage your MCP servers
  </Card>
  <Card title="API Reference" icon="code" href="/api-reference/introduction">
    Explore the complete API documentation
  </Card>
</CardGroup>