Resume Onepage Autofit Mcp

Name: Resume Onepage Autofit Mcp
Author: seriserendipia

@seriserendipia

About Resume Onepage Autofit Mcp

From Markdown to auto-one-paged PDF formatted resume, the last tool you need to automate your ai resume generation workflow.

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "resume-autofit": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/resume-onepage-autofit-mcp/mcp_server",
        "run",
        "mcp_server.py"
      ]
    }
  }
}

Tools

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Overview

What is Resume Onepage Autofit Mcp?

This MCP server automates the process of generating a single-page PDF resume from a user's experience. It integrates with AI agents (like Claude Desktop) to render Markdown content as a PDF, detect page overflow, and provide feedback for automatic content reduction to fit exactly one A4 page.

How to use Resume Onepage Autofit Mcp?

Install dependencies (Python 3.8+, Playwright, Chromium), configure the MCP server in Claude Desktop’s claude_desktop_config.json, prepare resume content in myexperience.md, then restart Claude and ask the AI to generate a single-page resume. The server is invoked automatically by the AI agent when it calls the render_resume_pdf tool.

Key features of Resume Onepage Autofit Mcp

Smart fitting: auto-adjusts content to fit one A4 page
Pixel-accurate page height detection via Playwright
Three-tier layered reduction strategy (format → content → deep)
Feedback loop: AI iterates based on overflow metrics
MCP integration: direct calls from Claude Desktop and other AI clients

Use cases of Resume Onepage Autofit Mcp

Quickly generate a single-page resume from raw experience text
Automate formatting and page-fitting without manual tweaking in Word
Integrate resume generation into an AI-assisted workflow
Produce consistent, clean PDFs for job applications

FAQ from Resume Onepage Autofit Mcp

What does this MCP do that a simple Markdown-to-PDF converter doesn't?

It actively detects overflow and provides structured feedback (overflow percentage and hints) so an AI agent can iteratively reduce content until the resume fits exactly one page, using a defined reduction strategy.

What are the runtime dependencies?

Python 3.8+, the Playwright library (v1.40+), and a Chromium browser (~150 MB first-time download). All dependencies are listed in requirements.txt and installed via pip or uv.

Where are the generated PDFs saved?

By default, PDFs are saved to the generated_resume/ folder in the project directory. You can customize the output path via a js/config.js file or by passing an output_path parameter when calling the tool.

What are the known limitations?

Requires Chromium (first-time download ~150 MB).
Very long resumes (10+ pages) may need multiple reduction rounds.
Some special characters (e.g., emoji) can affect layout.

What transport or authentication does the MCP server use?

The MCP server uses the standard MCP protocol (stdio transport) as configured in claude_desktop_config.json. No authentication is built-in; it runs locally.