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Convert GitHub commits into review-ready pull requests with Google Gemini

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Created by: Ahmed Salama || ahmedsalama

Ahmed Salama

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Last update a day ago

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Description

Categories
Developer Automation, AI Agents, GitHub Automation, DevOps Productivity

Build an AI-Driven GitHub Pull Request Automation with n8n + MCP

This workflow creates an AI-powered GitHub automation that turns raw commit history into a clean, professional pull request automatically.

When triggered via MCP or another workflow, it extracts repository details, fetches all commits from a target branch, uses AI to understand the intent behind the changes, and creates a well-structured pull request with a clear title and description.

The result is a reliable, no-manual-work system that standardizes pull requests and reduces review friction across teams.

Benefits

Consistent Pull Requests

Every PR follows a clean, readable structure regardless of who triggered it.

Zero Manual Formatting

No copy-pasting commit messages or writing descriptions by hand.

Faster Review Cycles

Reviewers get clear context upfront, reducing back-and-forth.

AI-Assisted Context Awareness

Commit history is summarized intelligently, not blindly concatenated.

MCP-Ready Automation

Can be called directly by AI tools like Cursor through MCP.

How It Works

MCP or Workflow Trigger

  • Triggered via MCP server or another n8n workflow
  • Accepts natural language or structured input

Repository Information Extraction

  • AI extracts:
    • Repository owner
    • Repository name
    • Source branch
    • Base branch

Commit Retrieval (GitHub API)

  • Fetches all commits for the source branch
  • Collects commit messages as context

Commit Summarization (AI)

  • AI analyzes commit history
  • Generates:
    • A concise PR title
    • A clear bullet-point description

Pull Request Creation

  • Creates a GitHub pull request automatically
  • Uses correct base and head branches
  • Inserts AI-generated title and description

Required Setup

GitHub

  • Repository access
  • OAuth or personal access token
  • Permission to read commits and create pull requests

AI Model

  • Google Gemini or compatible LLM
  • Connected via n8n AI nodes

n8n

  • Self-hosted or cloud
  • HTTP access to GitHub APIs
  • MCP Trigger enabled for AI tool access

Business Use Cases

Engineering Teams

  • Standardize PR quality across developers
  • Reduce cognitive load on contributors

DevOps & Platform Teams

  • Enforce PR hygiene automatically
  • Improve velocity without extra process

Founders & Tech Leads

  • Maintain clean repositories without micromanagement

Agencies & Consultants

  • Deliver AI-assisted GitHub automation to clients

Difficulty Level

Intermediate

Estimated Build Time

45–75 minutes

Monthly Operating Cost

  • GitHub: Existing plan
  • AI Model: Free tier or usage-based
  • n8n: Self-hosted or cloud

Typical range: $0–20/month

Why This Workflow Works

  • Commits are the most reliable source of change intent
  • AI summarizes meaning, not noise
  • MCP enables direct AI-to-automation execution
  • GitHub remains the single source of truth

Possible Extensions

  • Auto-assign reviewers based on files changed
  • Add PR labels using AI classification
  • Generate changelog entries automatically
  • Post PR summary to Slack or Teams
  • Enforce branch naming or commit standards

Details

Nodes used in workflow

  • MCP Trigger
  • AI Agent (Repository Extraction)
  • Structured Output Parser
  • GitHub API (Commits)
  • Summarize
  • AI LLM Chain
  • GitHub API (Create Pull Request)
  • If
  • Edit Fields (Set)
  • Sticky Note