Mastering MCP Servers in Google Antigravity: The Complete Advanced Guide

The Model Context Protocol (MCP) is one of Google Antigravity's most powerful features, enabling seamless integration with external tools, databases, APIs, and services. This comprehensive guide will take you from MCP basics to advanced custom server development.

New to Antigravity? Start with our installation guide first, then return here to supercharge your setup.

What is MCP (Model Context Protocol)?

MCP is an open protocol that allows AI assistants to securely connect with external data sources and tools. Think of it as a universal adapter that lets Google Antigravity communicate with virtually any service.

┌─────────────────────┐     MCP Protocol     ┌─────────────────────┐
│  Google Antigravity │ ◄──────────────────► │    MCP Server       │
│     (AI Client)     │   JSON-RPC over      │  (Tool Provider)    │
│                     │   stdio/HTTP         │                     │
└─────────────────────┘                      └─────────────────────┘
                                                      │
                                                      ▼
                                             ┌─────────────────┐
                                             │ External Service│
                                             │ (DB, API, etc.) │
                                             └─────────────────┘

Why MCP Matters

Without MCP

• AI can only see code in your editor
• Manual copy-paste of database schemas
• No access to external documentation
• Limited context for debugging

With MCP

• Direct database queries and exploration
• Real-time API documentation access
• GitHub issue and PR management
• Cloud service integration (AWS, GCP, Azure)
• Slack, Linear, Notion integration

Browse our MCP Server Directory for ready-to-use configurations.

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Getting Started with MCP

Configuration File Location

MCP servers are configured in your Antigravity settings file:

macOS/Linux:

~/.config/antigravity/mcp.json

Windows:

%APPDATA%\antigravity\mcp.json

Basic Configuration Structure

{
  "mcpServers": {
    "server-name": {
      "command": "executable",
      "args": ["arg1", "arg2"],
      "env": {
        "API_KEY": "your-key"
      }
    }
  }
}

Configuration issues? See our troubleshooting guide for MCP debugging tips.

---

Essential MCP Servers

1. Filesystem Server

Access and manipulate files beyond your project:

{
  "mcpServers": {
    "filesystem": {
      "command": "npx",
      "args": [
        "-y",
        "@anthropic-ai/mcp-filesystem",
        "/Users/username/projects",
        "/Users/username/documents"
      ]
    }
  }
}

Use Cases:

• Reading configuration files from other projects
• Accessing shared documentation
• Cross-project code analysis

2. GitHub Server

Full GitHub integration for issues, PRs, and repositories:

{
  "mcpServers": {
    "github": {
      "command": "npx",
      "args": ["-y", "@anthropic-ai/mcp-github"],
      "env": {
        "GITHUB_TOKEN": "ghp_xxxxxxxxxxxx"
      }
    }
  }
}

Capabilities:

• Create and manage issues
• Review and create pull requests
• Search repositories
• Analyze commit history
• Manage GitHub Actions

Example Prompts:

"Create an issue for the authentication bug we discussed"
"Review the latest PR and suggest improvements"
"Find all issues labeled 'bug' in the last week"

3. PostgreSQL Server

Direct database access for queries and schema exploration:

{
  "mcpServers": {
    "postgres": {
      "command": "npx",
      "args": ["-y", "@anthropic-ai/mcp-postgres"],
      "env": {
        "POSTGRES_CONNECTION_STRING": "postgresql://user:pass@localhost:5432/dbname"
      }
    }
  }
}

Features:

• Execute SELECT queries
• Explore table schemas
• Analyze relationships
• Generate migration scripts

Perfect for Python and API development workflows.

4. MongoDB Server

NoSQL database integration:

{
  "mcpServers": {
    "mongodb": {
      "command": "npx",
      "args": ["-y", "@anthropic-ai/mcp-mongodb"],
      "env": {
        "MONGODB_URI": "mongodb+srv://user:pass@cluster.mongodb.net/dbname"
      }
    }
  }
}

5. Slack Server

Team communication integration:

{
  "mcpServers": {
    "slack": {
      "command": "npx",
      "args": ["-y", "@anthropic-ai/mcp-slack"],
      "env": {
        "SLACK_BOT_TOKEN": "xoxb-xxxxxxxxxxxx"
      }
    }
  }
}

6. AWS Server

Amazon Web Services integration:

{
  "mcpServers": {
    "aws": {
      "command": "npx",
      "args": ["-y", "@anthropic-ai/mcp-aws"],
      "env": {
        "AWS_ACCESS_KEY_ID": "AKIAXXXXXXXX",
        "AWS_SECRET_ACCESS_KEY": "xxxxxxxx",
        "AWS_REGION": "us-east-1"
      }
    }
  }
}

Services Supported:

• S3 bucket management
• Lambda function inspection
• DynamoDB queries
• CloudWatch logs

---

Advanced MCP Configuration

Multiple Server Setup

Run multiple MCP servers simultaneously:

{
  "mcpServers": {
    "filesystem": {
      "command": "npx",
      "args": ["-y", "@anthropic-ai/mcp-filesystem", "/projects"]
    },
    "github": {
      "command": "npx",
      "args": ["-y", "@anthropic-ai/mcp-github"],
      "env": { "GITHUB_TOKEN": "ghp_xxx" }
    },
    "postgres-prod": {
      "command": "npx",
      "args": ["-y", "@anthropic-ai/mcp-postgres"],
      "env": { "POSTGRES_CONNECTION_STRING": "postgresql://prod-url" }
    },
    "postgres-dev": {
      "command": "npx",
      "args": ["-y", "@anthropic-ai/mcp-postgres"],
      "env": { "POSTGRES_CONNECTION_STRING": "postgresql://dev-url" }
    }
  }
}

Secure Credential Management

Never hardcode credentials. Use environment variables:

# ~/.zshrc or ~/.bashrc
export GITHUB_TOKEN="ghp_xxxxxxxxxxxx"
export POSTGRES_URL="postgresql://..."
export SLACK_TOKEN="xoxb-xxxxxxxxxxxx"

Then reference in config:

{
  "mcpServers": {
    "github": {
      "command": "npx",
      "args": ["-y", "@anthropic-ai/mcp-github"],
      "env": { "GITHUB_TOKEN": "${GITHUB_TOKEN}" }
    }
  }
}

---

Building Custom MCP Servers

When to Build Custom Servers

• Proprietary internal APIs
• Custom business logic
• Specialized data sources
• Unique workflow requirements

Complete Custom Server Example

Let's build a server for a custom CRM:

// crm-mcp-server/index.ts
import { Server, Tool } from "@anthropic-ai/mcp-server";

class CRMServer {
  private server: Server;
  private apiKey: string;
  private baseUrl: string;

  constructor() {
    this.apiKey = process.env.CRM_API_KEY!;
    this.baseUrl = process.env.CRM_BASE_URL!;
    
    this.server = new Server({
      name: "crm-server",
      version: "1.0.0",
      description: "Custom CRM integration"
    });

    this.registerTools();
  }

  private registerTools() {
    // Tool 1: Search customers
    this.server.addTool({
      name: "search_customers",
      description: "Search for customers by name, email, or status",
      parameters: {
        type: "object",
        properties: {
          query: { type: "string", description: "Search query" },
          status: { 
            type: "string", 
            enum: ["active", "inactive", "lead"]
          },
          limit: { type: "number", default: 10 }
        }
      },
      handler: async ({ query, status, limit }) => {
        const customers = await this.searchCustomers(query, status, limit);
        return JSON.stringify(customers);
      }
    });

    // Add more tools...
  }

  start() {
    this.server.start();
  }
}

const crmServer = new CRMServer();
crmServer.start();

---

MCP Best Practices

1. Security First

• Never expose write access to production databases
• Use read-only credentials where possible
• Implement rate limiting in custom servers
• Audit all MCP server access

2. Performance Optimization

• Cache frequently accessed data
• Implement connection pooling
• Use pagination for large datasets
• Set appropriate timeouts

3. Error Handling

server.addTool({
  name: "safe_query",
  handler: async (params) => {
    try {
      const result = await dangerousOperation(params);
      return JSON.stringify({ success: true, data: result });
    } catch (error) {
      return JSON.stringify({ 
        success: false, 
        error: error.message
      });
    }
  }
});

---

MCP + Agent Mode Integration

MCP servers become even more powerful with Agent Mode:

Example Workflow:

MCP Servers Active:
- postgres (database)
- github (version control)
- slack (notifications)

Prompt: "Create a feature branch, implement user analytics,
         and notify the team when done"

Agent Mode with MCP:
1. github: Create branch "feature/analytics"
2. postgres: Query schema for user tables
3. Write analytics code
4. Run tests
5. github: Commit and push
6. github: Create pull request
7. slack: Post update to #dev channel

---

Troubleshooting MCP Issues

Server Not Starting

# Check if server runs manually
npx -y @anthropic-ai/mcp-github

# Check logs
tail -f ~/.config/antigravity/logs/mcp-*.log

Connection Errors

1. Verify credentials are correct
2. Check network connectivity
3. Ensure environment variables are set
4. Review firewall settings

For more solutions, see our complete troubleshooting guide.

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Explore More MCP Servers

Browse our MCP Server Directory for:

• Pre-configured server setups
• Community contributions
• Integration tutorials

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Next Steps

1. Browse MCP Directory - Find servers for your stack
2. Master Agent Mode - Combine MCP with automation
3. Explore Use Cases - Real-world implementations
4. Best Practices - Development patterns
5. Join Community - Share your custom servers

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Last updated: December 2025

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• Installation Guide
• Agent Mode Mastery
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• Troubleshooting Guide