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Build an Agentic Workflow with CrewAI and GitHub MCP Server Tools

PROJECT

Build an Agentic Workflow with CrewAI and GitHub MCP Server Tools

In this project, we’ll learn to build a CrewAI agentic workflow using GitHub MCP Server tools. We’ll fetch and summarize issues, PRs, and branches and convert Markdown into polished HTML reports.

You will learn to:

Run and validate GitHub MCP Server commands locally to fetch the repo data.

Use LangChain to turn MCP commands into reusable tools.

Build and manage a multi-agent Crew workflow.

Integrate CrewAI with a Django application.

Skills

Generative AI

Large Language Models (LLMs)

Web Development

Prerequisites

Experience with Python programming

Working knowledge of Django

Intermediate understanding of large language models (LLMs) and prompt-based workflows

Familiarity with CrewAI concepts (agents, tasks, and crews)

Understanding of REST APIs

Technologies

OpenAI

Django

Python

LangChain

Project Description

This Django-based project demonstrates an agentic framework for integrating GitHub repository insights into a web application using CrewAI and the GitHub MCP Server. The app allows users to input a public GitHub repository URL, triggering an agentic CrewAI workflow. This workflow orchestrates multiple specialized agents, each responsible for retrieving and summarizing different aspects of the repository, including open issues, recent pull requests, and existing branches.

These CrewAI agents are powered by structured tools interacting with the GitHub MCP Server to extract relevant data. Each agent’s task output is written as Markdown documentation files, which are then combined and rendered into a clean HTML report. This project is ideal for developers looking to understand multi-agent orchestration using CrewAI’s agentic capabilities, the practical use of LangChain tools interacting with an MCP Server, and dynamic document generation in Django.

Project Tasks

Introduction

Task 0: Get Started

Integrate GitHub MCP Server

Task 1: Build mcpcurl

Task 2: Explore the GitHub MCP Server

Build and Run Django Application

Task 3: Build the User Interface

Task 4: Render the Documentation Interface

Task 5: Run the Django Application

Build the GitHub MCP Server Crew

Task 6: Set Up the CrewAI Project Structure

Task 7: Create a Custom Tool to Analyze a Repository’s Structure

Task 8: Create the CrewAI Agent to Analyze Repository Structure

Task 9: Set Up the CrewAI Task to Summarize Repository Structure

Task 10: Assemble the CrewAI Workflow

Task 11: Integrate Your Crew into the Django Workflow

Task 12: Run the Application

Task 13: Build an Issue Analyzer Agent

Task 14: Add the Issue Lister Task to the Crew

Task 15: Build the Pull Request Lister Agent

Task 16: Add the Pull Request Task to the Crew

Task 17: Build the Branch Lister Agent

Task 18: Add the Branch Listing Task to the Crew

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Pradip Pariyar

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"This was an excellent lesson. I learned a lot working through the process. I enjoyed it so much that I rebuilt it my AWS account to see how hard it would be to deploy to a production environment."

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Senior Software Engineer

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Senior Software Engineer

Relevant Courses

Use the following content to review prerequisites or explore specific concepts in detail.