ATS Engine MCP server

An MCP server that lets an AI assistant (Claude, Cursor, VS Code Copilot and others) read your own resume the way an applicant tracking system (ATS) does, and score it with @veriworkly/ats-engine's published, deterministic rubric.

Ask your assistant things like "check my resume at ~/Documents/cv.pdf", "how well does it match this job posting?", "why did it fail the date check?" or "show me how an ATS reads my resume".

The score comes from the rubric (RUBRIC.md), not from a model. The same file always gets the same score. The assistant explains the result and helps you fix what failed.

Install

You need Node.js 22.12 or later. Every client below runs the server with npx -y @veriworkly/ats-engine-mcp.

Claude Code

claude mcp add ats-engine -- npx -y @veriworkly/ats-engine-mcp

On native Windows (not WSL), wrap npx in cmd /c:

claude mcp add ats-engine -- cmd /c npx -y @veriworkly/ats-engine-mcp

Claude Desktop

Open Settings → Developer → Edit Config, add the server to claude_desktop_config.json, and restart Claude Desktop:

{
  "mcpServers": {
    "ats-engine": {
      "command": "npx",
      "args": ["-y", "@veriworkly/ats-engine-mcp"]
    }
  }
}

Cursor

Add it to ~/.cursor/mcp.json (every project) or .cursor/mcp.json (one project):

{
  "mcpServers": {
    "ats-engine": {
      "command": "npx",
      "args": ["-y", "@veriworkly/ats-engine-mcp"]
    }
  }
}

VS Code

Add it to .vscode/mcp.json in your workspace, or run MCP: Add Server from the Command Palette:

{
  "servers": {
    "ats-engine": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "@veriworkly/ats-engine-mcp"]
    }
  }
}

Tools

Every tool returns readable text for the assistant and its result as structured JSON (structuredContent, described by each tool's outputSchema).

The resource rubric://default is the whole rubric as JSON.

Inputs.

• Resume files: .pdf, .docx, .html, .txt, .md, or a .json JSON Resume or ats-resume document. Postings: .txt, .md, .pdf, .docx, or a saved .html page.
• Give absolute paths. ~/ is read as your home folder; any other relative path is read from the folder the server was started in.
• Pasted text and job_text may be up to 200 000 characters.
• Files over 20 MB are refused, and so are folders, pipes, devices and network paths (\\host\share\…). So is a PDF with no text layer: an ATS cannot read a scan either.
• region is US, DE or IN. Without it, the region is inferred from the resume.
• target_ats is greenhouse, lever or taleo. It adds what that vendor documents publicly, each note with a link to the vendor's page. It never changes the score.

Advice. check_resume ends with advice, a list that is never scored. For a file (not pasted text) it covers the name (Resume_final_v3 (2).pdf reads as a draft; a Firstname-Lastname-Resume.pdf name is suggested), a size over 2 MB, a password, and tracked changes or comments left in a Word document. For a US resume it also covers details that can invite age bias. With target_ats it adds the vendor's notes.

Privacy

The server runs on your computer, over stdio. It makes no network requests and calls no AI model. It reads only the files you name in a request, and nothing leaves your machine except what your assistant itself sends to its model provider: the tool results it reads, which include text from your resume.

Intended use

A score measures how well a resume parses and reads. It says nothing about the person.

From source

git clone https://github.com/VeriWorkly/ats-engine.git
cd ats-engine
npm ci
npm run build
claude mcp add ats-engine -- node "$PWD/packages/mcp/dist/index.js"

License

MIT