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KhushalB25

resume-scorer-mcp

by KhushalB25
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resume-scorer-mcp

MCP server that scores a structured resume against a deterministic 4-category engineering rubric. Numeric score, evidence per category, bonus points, deductions, concrete improvement areas — all without an LLM call.

MIT License Node ≥ 18 MCP

What it scores

Four categories tuned for modern engineering profiles:

Category

Max

Open Source contributions

35

Self Projects

30

Production Experience

25

Technical Skills

10

Bonus (portfolio, LinkedIn, etc.)

+20

Deductions (missing links, tutorial projects)

up to −15

Total

100 (+20 bonus)

Related MCP server: decroche-mcp

Why use it

  • Candidates — self-check before applying. Iterate until score crosses your target.

  • Recruiters — bulk-screen JSON Resumes without sending content to a paid LLM.

  • AI agents — a deterministic scoring primitive for agent workflows.

  • Privacy — no resume content leaves your machine.

Install

npm install -g resume-scorer-mcp

Or run directly via npx:

npx resume-scorer-mcp

Use with Claude Desktop

Add to claude_desktop_config.json:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

  • Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "resume-scorer": {
      "command": "npx",
      "args": ["-y", "resume-scorer-mcp"]
    }
  }
}

Restart Claude Desktop. Ask:

"Score this resume against the rubric" + paste a JSON Resume

Tools

score_resume

Score a structured resume in JSON Resume format.

{
  "resume_json": {
    "basics": {
      "name": "Your Name",
      "url": "https://yoursite.dev",
      "profiles": [
        { "network": "GitHub",   "url": "https://github.com/you" },
        { "network": "LinkedIn", "url": "https://linkedin.com/in/you" }
      ]
    },
    "work": [
      { "name": "Company", "startDate": "2025-03", "endDate": "2026-04",
        "highlights": ["Built X with Y …"] }
    ],
    "projects": [
      { "name": "Project", "url": "https://project.dev",
        "description": "Real-time LLM thing using OpenAI/Claude…",
        "technologies": ["Next.js", "Firebase", "OpenAI"] }
    ],
    "skills": [{ "name": "Languages", "keywords": ["Python", "TypeScript", "React"] }]
  }
}

Also accepts resume_json_path (absolute path) instead of inline data.

score_resume_from_freeform

Best-effort scoring of plain text. Less accurate. Use score_resume when possible.

Example response

{
  "scores": {
    "open_source":     { "score": 6,  "max": 35, "evidence": "GitHub URL present but no external contributions detected …" },
    "self_projects":   { "score": 22, "max": 30, "evidence": "Per-project breakdown: Project: 3 complexity signals, link present -> 8/10 …" },
    "production":      { "score": 19, "max": 25, "evidence": "~3.1 years total production tenure across 3 role(s) (LLM production weighting +2)." },
    "technical_skills":{ "score": 9,  "max": 10, "evidence": "18 distinct technologies/keywords detected." }
  },
  "bonus_points": { "total": 3, "breakdown": "+2 portfolio URL - +1 LinkedIn profile" },
  "deductions":   { "total": 2, "reasons":   "-2 for 1 project(s) without links: …" },
  "key_strengths": [
    "Solid production tenure with multi-year track record.",
    "Personal projects show technical depth and shipped artefacts.",
    "Broad polyglot stack signal."
  ],
  "areas_for_improvement": [
    "Land 2-3 merged pull requests to popular open-source repos to break out of the <=10 self-only cap.",
    "Add live demo or repo URL to every project to remove missing-link deductions."
  ],
  "total": 59,
  "max_total": 100
}

Local development

git clone https://github.com/KhushalB25/resume-scorer-mcp.git
cd resume-scorer-mcp
npm install
npm run build
npm start

Test with @modelcontextprotocol/inspector:

npx @modelcontextprotocol/inspector node dist/index.js

Rubric design

The scoring rubric is the author's own design. Bands are tuned for early-career to mid-career software engineers. Categories and weightings can be customised by forking src/index.ts — pure functions, no external scoring service.

Author

Khushal Bhandari · GitHub

License

MIT

Install Server
A
license - permissive license
A
quality
B
maintenance

How are these scores calculated?

Maintenance

–Maintainers
–Response time
–Release cycle
–Releases (12mo)
Commit activity

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Tools

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