resume-forge-mcp 0.3.6

MCP server for intelligent LaTeX resume generation — browse 350+ Overleaf templates, auto-compile with pdflatex/xelatex/lualatex, tailor to job descriptions, ATS scoring, and visual preview.

LaTeX Resume MCP

An MCP (Model Context Protocol) server for intelligent LaTeX resume generation with visual verification, quality scoring, and job description tailoring.

Features

• Data-driven resumes: Store resume content in JSON, generate LaTeX on demand
• Visual verification: Preview rendered PDFs as images directly in Claude
• Quality scoring: Bullet analysis, ATS compatibility checks, keyword matching
• Job tailoring: Auto-select and prioritize content based on job descriptions
• Variant management: Create multiple resume versions for different roles
• LaTeX compilation: Generate publication-quality PDFs using pdflatex

Installation

Using uvx (recommended)

uvx latex-resume-mcp

Using pip

pip install latex-resume-mcp

Configuration

Add to your Claude Desktop config file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json

Using uvx

{
  "mcpServers": {
    "latex-resume": {
      "command": "uvx",
      "args": ["latex-resume-mcp"]
    }
  }
}

Using pip installation

{
  "mcpServers": {
    "latex-resume": {
      "command": "latex-resume-mcp"
    }
  }
}

Custom directories (optional)

{
  "mcpServers": {
    "latex-resume": {
      "command": "uvx",
      "args": ["latex-resume-mcp"],
      "env": {
        "LATEX_RESUME_DATA_DIR": "/path/to/data",
        "LATEX_RESUME_OUTPUT_DIR": "/path/to/output"
      }
    }
  }
}

Prerequisites

LaTeX Installation

To compile resumes to PDF, you need LaTeX installed:

macOS:

brew install --cask mactex
# or for a smaller installation:
brew install --cask basictex

Ubuntu/Debian:

sudo apt install texlive-latex-base texlive-latex-extra texlive-fonts-extra

Windows: Download and install MiKTeX

Available Tools (15)

Data Management

Tool	Description
import_from_latex_file	Parse existing .tex file into structured JSON data
get_resume_data	Get the master resume data pool
update_resume_data	Add, edit, or remove entries (experience, projects, etc.)
list_variants	List all saved resume variants
get_variant	Get details of a specific variant
save_variant	Create or update a variant configuration

Generation & Compilation

Tool	Description
generate_resume	Generate .tex file from data (optionally using a variant)
compile_resume_tex	Compile .tex to PDF using pdflatex
compile_and_preview	Compile and return preview images
preview_resume	Preview an existing PDF as images

Intelligence

Tool	Description
score_resume_quality	Score bullets, check ATS compatibility, match keywords
parse_job_description_text	Extract keywords and requirements from job description
generate_tailored_resume	Auto-select content based on JD, compile, and preview

Utility

Tool	Description
assess_quality	Run programmatic checks (page count, encoding, overflow)
get_config	Show current configuration and available tools

Usage Examples

Basic Workflow

> Get my resume data
Shows all stored experience, projects, education, skills

> Generate my resume and compile it
Creates .tex file and compiles to PDF

> Preview my resume
Returns rendered images of each page

Quality Improvement

> Score my resume quality
Returns bullet scores, ATS report, improvement suggestions

> Score my resume against keywords: Python, AWS, Kubernetes
Shows keyword match percentage and missing terms

Job Tailoring

> Parse this job description: [paste JD text]
Extracts title, required skills, preferred skills, keywords

> Generate a tailored resume for this job description
Auto-selects most relevant experience/projects, reorders skills, compiles

Variant Management

> List my resume variants
Shows: swe, ml_engineer, backend, etc.

> Save a new variant called "startup" with experiences 0,1,3
Creates variant configuration

> Generate my resume using the startup variant
Uses variant's content selection and ordering

Data Model

Resume data is stored as JSON with these sections:

• contact: Name, email, phone, LinkedIn, GitHub
• education: Degrees with GPA, dates, coursework
• publications: Academic publications
• experience: Work history with bullets and tags
• projects: Personal/open-source projects with tags
• skills: Categorized skill lists

Each experience and project can have tags (e.g., ["swe", "ml", "cloud"]) for intelligent content selection.

Default Directories

• Data: ~/.latex-resumes/data/ (resume JSON and variants)
• Output: ~/.latex-resumes/output/ (generated .tex and .pdf files)

License

MIT