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resume-parser-mcp

Extracts structured candidate data like name, skills, experience, and education from resumes or CVs in any format using Claude AI. Recruiters and developers integrate it into applicant tracking systems (ATS) or screening workflows to automate parsing of job applications. Supports processing PDFs, Word docs, and text files for consistent data output.

resume-parsing
ai-extraction
hr-tech
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Overview

The resume-parser-mcp server provides an MCP interface to parse resumes and CVs, converting unstructured documents into structured JSON data using Claude AI. It handles various formats including PDF, DOCX, and plain text, outputting fields such as contact info, work history, skills, and qualifications.

Key Capabilities

  • Resume parsing: Uploads a resume file or text, applies Claude AI to identify and extract key sections (e.g., personal details, professional summary, employment history, education, certifications, skills). Returns JSON with standardized fields for easy integration.
  • No additional tools listed; core function focuses on AI-driven extraction accuracy across diverse resume layouts and languages.

Use Cases

  1. ATS Integration: Developers connect the server to an applicant tracking system, automatically parsing incoming resumes to populate candidate profiles with structured data like experience and skills arrays.

  2. Recruiter Screening: HR teams upload batches of CVs to extract work_history and education details, enabling quick filtering by criteria such as years of experience or specific skills.

  3. Job Board Processing: Platforms ingest user-submitted resumes, using the parser to structure data for database storage and search functionality.

  4. Talent Analytics: Research teams analyze parsed data from multiple resumes to generate reports on skill trends or demographic insights.

Who This Is For

Recruiters and HR professionals needing fast, accurate resume processing; developers building recruitment tools or ATS extensions; data analysts working with candidate datasets. Ideal for teams handling high-volume applications without manual data entry.

PlaygroundUpdated Apr 8, 2026