resume_updater

An AI-powered tool that automatically tailors your resume for specific job applications using the Model Context Protocol (MCP) agent framework.

Project Overview

This tool analyzes your current resume, GitHub repositories, and a job posting to generate a tailored resume that highlights relevant skills and experiences for the target position.

Future

1. Enhanced Web Scraping

   • Implement advanced web scraping capabilities to handle JavaScript-rendered content and iframes
   • Explore integration with tools like Selenium or Playwright for dynamic content retrieval

2. Interactive User Interface

   • Develop a Streamlit-based chat interface for a more intuitive user experience
   • Provide GUI-based configuration of input.json as an alternative to manual editing
   • Enable real-time resume previews and adjustments

3. HTML-Based Resume Generation

   • Pivot from Markdown to HTML for greater control over formatting
   • Implement custom CSS styling for precise layout management
   • Maintain clean, semantic markup for accessibility

4. Page Length Optimization

   • Integrate PDF page length validation into the evaluator-optimizer workflow
   • Add automated font size and margin adjustments while preserving readability

5. More Isolated Agents/Prompts

   • Break down current monolithic agents into focused, single-task components
     • Resume analyzer
     • Job requirements extractor
     • Content optimizer
     • Format validator
   • Store prompts in separate YAML files for easy testing and iteration
   • Implement basic unit tests with mock responses

Approach

1. Input Processing

   • Reads and parses existing resume from PDF
   • Analyzes specified GitHub repositories for project details
   • Extracts requirements from job posting URL and description file
     • Caveat: The fetch-mcp server retrieves only web content present in HTML. To handle more complex content, such as JavaScript-rendered iFrames, additional MCP servers must be utilized in the future.

2. Content Optimization

   • Aggregates information from all sources
   • Uses an evaluator-optimizer workflow to generate optimized content
   • Ensures output maintains professional formatting and fits one page

3. Quality Control

   • Evaluates resume for relevance to job requirements
   • Verifies clear demonstration of skills
   • Checks formatting and length constraints

4. Output Generation

   • Generates the final resume in markdown format
   • Pauses to allow the user to review and tweak the tailored resume

Technologies Used

• MCP Agent Framework: Core orchestration system for AI agents
• OpenAI: Powers the AI agents for content analysis and generation
• MCP Servers:
  • fetch-mcp: Handles URL content retrieval
  • markdownify-mcp: Converts between formats
  • filesystem-mcp: Manages file operations
  • markdown2pdf-mcp: Converts markdown to PDF format

Setup Instructions

Python Dependencies

1. Install Poetry (if not already installed): Follow the instructions from the official Poetry documentation.

2. Navigate to Your Project Directory:

   cd /home/bnoffke/repos/resume_updater
   

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3. Install the Python Dependencies:

   poetry install
   

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npm Dependencies

1. Ensure Node.js and npm are Installed: You can download and install them from Node.js official website.

2. Navigate to Your Project Directory:

   cd /home/bnoffke/repos/resume_updater
   

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3. Install the npm Dependencies:

   npm install
   

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Install pnpm

1. Install pnpm (required for some dependencies):

   npm install -g pnpm
   

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   Or follow alternative installation methods from the pnpm documentation.

Additional Requirements

1. Setup markdown2pdf-mcp server:

   • Clone the repository from markdown2pdf-mcp
   • Follow the installation instructions in the repository's README

2. Setup markdownify-mcp server:

   • Clone the repository from markdownify-mcp
   • Install dependencies: pnpm install
   • Build the project: pnpm run build

3. Setup fetch-mcp server:

   • Clone the repository from fetch-mcp
   • Install dependencies: npm install
   • Build the project: npm run build

4. Configure MCP Servers Use the provided mcp_agent.config.yaml file in the repository as a reference and update the paths according to your local installations of the MCP servers.

Usage

1. Create or modify input.json with your configuration:

{
    "root_path": "/path/to/resume/directory",
    "resume_path": "current_resume.pdf",
    "github_repos": [
        "https://github.com/username/repo1",
        "https://github.com/username/repo2"
    ],
    "job_posting_url": "https://example.com/job-posting",
    "job_description_path": "job_description.txt",
    "output_path": "tailored_resume",
    "additional_info": "additional_info.txt"
}

2. Run the script with the config flag:

poetry run python resume_updater.py --config input.json

Configuration Parameters

• root_path: Base directory where your resume files are stored
• resume_path: Path to your current resume in PDF format (relative to root_path)
• github_repos: List of GitHub repository URLs that showcase relevant work
• job_posting_url: URL of the job posting to analyze
• job_description_path: Path to a text file containing additional job description details (relative to root_path)
• output_path: Base name for output files (will create both .md and .pdf, relative to root_path)
• additional_info: Optional path to a text file containing additional information to incorporate (relative to root_path)

The script will:

1. Generate a markdown file at {root_path}/{output_path}.md
2. Pause for your review and modifications
3. Create the final PDF at {root_path}/{output_path}.pdf using markdown2pdf-mcp server