MCP Integration Deep Dive

Reading time: 25 minAdvanced

Build custom integrations with Model Context Protocol to extend Claude Code and connect it with your existing toolchain.

Understanding Model Context Protocol

Model Context Protocol (MCP) is the foundation of Claude Code's ability to understand and work with your codebase. By leveraging MCP, you can create powerful integrations that enhance Claude's capabilities.

What is MCP?

Model Context Protocol is a standardized way to provide context to language models about code, files, and project structure. It enables Claude to:

  • Understand code relationships across multiple files
  • Track changes over time
  • Maintain awareness of project structure
  • Interface with external tools and services

MCP Components

The protocol consists of several key components:

  • Context Managers - Handle gathering and processing of code context
  • Schema Definitions - Standardize how information is formatted
  • Connectors - Enable communication between different systems
  • Extensions - Add custom functionality to the protocol

Setting Up Your Development Environment

Before diving into MCP integration, you'll need to set up your development environment:

Prerequisites

  • Node.js 18+ and npm/yarn
  • Claude Code CLI installed and authenticated
  • Basic understanding of APIs and protocols
  • Familiarity with TypeScript (recommended)

Installing MCP Libraries

Install the required packages:

npm install @anthropic/mcp-core @anthropic/mcp-connectors

This installs the core MCP library and the connectors module for building integrations.

Building Your First Integration

Let's build a simple integration that connects Claude Code with an external API:

1. Create Your Integration Project

mkdir claude-integration-example
cd claude-integration-example
npm init -y
npm install typescript ts-node @types/node --save-dev
npx tsc --init

2. Define Your Connector

Create a file named connector.ts:

import { MCPConnector, ConnectorConfig } from '@anthropic/mcp-connectors';

class MyApiConnector extends MCPConnector {
  constructor(config: ConnectorConfig) {
    super(config);
    // Initialize your connector
  }

  async fetchData(query: string): Promise<any> {
    // Implement your API fetching logic
    const response = await fetch('https://api.example.com/data?q=' + encodeURIComponent(query));
    return response.json();
  }

  async processContext(context: any): Promise<any> {
    // Process and transform the context
    return {
      ...context,
      enriched: true,
      timestamp: new Date().toISOString()
    };
  }
}

export default MyApiConnector;

3. Register Your Connector

Create a file named index.ts:

import { MCPRegistry } from '@anthropic/mcp-core';
import MyApiConnector from './connector';

// Register your connector
MCPRegistry.register('my-api-connector', {
  connector: MyApiConnector,
  config: {
    apiKey: process.env.API_KEY,
    baseUrl: 'https://api.example.com'
  }
});

// Start the MCP service
MCPRegistry.start();

4. Build and Run

npx tsc
node dist/index.js

This will compile your TypeScript and start your MCP integration service.

Advanced Integration Techniques

Once you've built a basic integration, you can explore more advanced techniques:

Custom Context Processors

Create specialized processors for different types of context:

class CodebaseProcessor {
  processFile(file: string, content: string): any {
    // Process file content based on file type
    if (file.endsWith('.js')) {
      return this.processJavaScript(content);
    } else if (file.endsWith('.py')) {
      return this.processPython(content);
    }
    return content;
  }

  // Specialized processors
  processJavaScript(content: string): any {
    // JavaScript-specific processing
  }

  processPython(content: string): any {
    // Python-specific processing
  }
}

Bi-directional Integrations

Create integrations that both provide context to Claude and receive commands from Claude:

class BiDirectionalConnector extends MCPConnector {
  // ... initialization code ...

  // Receive commands from Claude
  async receiveCommand(command: string, params: any): Promise<any> {
    switch (command) {
      case 'fetch-dependencies':
        return this.fetchDependencies(params.project);
      case 'run-tests':
        return this.runTests(params.testPath);
      default:
        throw new Error(`Unknown command: ${command}`);
    }
  }

  // Command implementations
  async fetchDependencies(project: string): Promise<any> {
    // Implementation
  }

  async runTests(testPath: string): Promise<any> {
    // Implementation
  }
}

Real-world Integration Examples

Here are some practical examples of MCP integrations:

CI/CD Integration

Connect Claude Code to your CI/CD pipeline to automate code reviews, testing, and deployment.

  • Automate PR reviews
  • Generate test cases
  • Validate changes against style guides
  • Create deployment documentation

Documentation Generator

Build an integration that automatically generates and updates documentation from code.

  • Generate API documentation
  • Create user guides
  • Document code architecture
  • Keep README files updated

Issue Tracker Integration

Connect Claude Code with issue tracking systems like JIRA or GitHub Issues.

  • Auto-generate issue descriptions
  • Link code changes to issues
  • Suggest fixes for reported bugs
  • Prioritize technical debt

Database Schema Manager

Create an integration that helps manage database schemas and migrations.

  • Generate migration scripts
  • Document schema changes
  • Analyze query performance
  • Suggest index optimizations

Next Steps

Continue your journey with MCP integrations by exploring these resources: