Read the full article on DataCamp: Model Context Protocol (MCP): A Guide With Demo Project

Learn how to build a PR review server using Anthropic’s Model Context Protocol (MCP) that connects Claude Desktop with GitHub and Notion for dynamic code analysis and documentation.

Overview

The Model Context Protocol (MCP) is an open standard introduced by Anthropic to streamline communication between language models and external tools such as APIs, databases, or applications like GitHub and Notion.

In this tutorial, you’ll build a complete MCP-based PR Review system where Claude Desktop acts as the AI agent analyzing pull requests. It connects with GitHub to fetch code diffs and stores review summaries to Notion — all using MCP’s standardized server-client interface.

Why Use MCP?

MCP enables AI tools to interact with external systems efficiently and securely. Some key advantages include:

  • Standardized integration: Consistent protocol for interacting with APIs and tools.
  • Flexible transports: Supports stdio, WebSockets, HTTP SSE, and UNIX sockets.
  • Modularity: Swap models (Claude, GPT, etc.) or tools without rewriting logic.
  • Security: Keeps sensitive data within your infrastructure.

Project Overview: Claude-Powered PR Review Agent

In this demo, we’ll implement:

  • ✅ GitHub Integration: Fetch PR metadata and file changes using REST API.
  • 🤖 Claude Desktop Agent: Analyze diffs and suggest improvements.
  • 🧾 Notion Integration: Save review results to a Notion page.
  • 🔌 MCP Server: Provide these tools to Claude via the MCP standard.

Step-by-Step Implementation

Step 1: Environment Setup

Install the uv Python package manager and initialize the project:

curl -LsSf https://astral.sh/uv/install.sh | sh
uv init pr_reviewer
cd pr_reviewer
uv venv
source .venv/bin/activate

Step 2: Install Dependencies

Install required packages using uv:

uv add "mcp[cli]" requests python-dotenv notion-client

Or using requirements.txt:

requests>=2.31.0
python-dotenv>=1.0.0
mcp[cli]>=1.4.0
notion-client>=2.3.0

Then run:

uv pip install -r requirements.txt

Step 3: Configure Environment Variables

Create a .env file:

GITHUB_TOKEN=your_github_token
NOTION_API_KEY=your_notion_api_key
NOTION_PAGE_ID=your_notion_page_id

Generate:

  • A GitHub token from Developer Settings → Personal Access Tokens
  • A Notion integration token and page ID from Notion Integrations

Step 4: GitHub Integration Module

Create a file github_integration.py to fetch PR data:

def fetch_pr_changes(repo_owner: str, repo_name: str, pr_number: int) -> dict:
    # Uses GitHub REST API to get metadata and file diffs
    ...

This module extracts PR title, description, file diffs, patch details, and more using GitHub’s authenticated API.

Step 5: Build the MCP Server

Create a file pr_analyzer.py and define a server using FastMCP:

from mcp.server.fastmcp import FastMCP

class PRAnalyzer:
    def __init__(self):
        self.mcp = FastMCP("github_pr_analysis")
        ...

Register tools:

  1. fetch_pr() → fetches GitHub PR info
  2. create_notion_page() → creates a Notion page with Claude’s output

These tools become available to Claude via the MCP plug icon in Claude Desktop.

Step 6: Run the MCP Server

Start the MCP server:

python pr_analyzer.py

In Claude Desktop, you’ll now see a 🔌 plug icon and 🔨 tools interface.

You can input any GitHub PR link, and Claude will:

  • Fetch the PR metadata and file changes
  • Analyze diffs
  • Summarize the PR and optionally upload the result to Notion

Use Cases and Extensions

This MCP workflow can be extended into many directions:

  • 🔄 Auto-sync PR reviews to Slack or Teams
  • 📊 Track review insights in dashboards
  • ✅ Automate PR acceptance/rejection based on review
  • 🛠 Integrate with Jira/Trello for ticket management

Conclusion

This tutorial showed you how to create a modular, AI-powered PR review agent using Anthropic’s MCP, Claude Desktop, GitHub, and Notion. With MCP’s open standard, your tools and models remain decoupled, secure, and scalable.

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