HireLayer MCP server

HireLayer MCP Server

Resume parsing, candidate matching and candidate ranking for AI agents.

The official Model Context Protocol server for HireLayer. Parse resumes and CVs, turn job descriptions into criteria, then score and rank candidates from Claude, ChatGPT, Cursor, VS Code, Codex or any MCP client.

Server URL: https://hirelayer.co/mcp · sign in with your HireLayer account, no API key to copy.

"Screen these 3 resumes against the Senior React job and tell me who to interview."

Your assistant parses each CV, extracts the job criteria, scores every candidate criterion by criterion and explains the shortlist.

Contents

• What you can do
• Quick start
• Install in your MCP client
• Tools
• Example prompts
• Pricing and credits
• Data and privacy
• Troubleshooting
• FAQ

What you can do

• Parse resumes and CVs. Turn PDF, Word, image and other files into structured JSON: contact details, work experience, education, languages, skills and the full text. Scanned resumes go through OCR, and the resume language is detected.
• Turn a job description into criteria. Get weighted, explained matching criteria, with mandatory requirements flagged.
• Match candidates to jobs. Score a resume against a job from 0 to 1, with an explanation for each criterion.
• Rank candidates. Order up to 10 candidates for the same job in one call, with a score and a rationale for each.
• Normalize skills. Map free-text skills in French or English to a skills taxonomy with stable IDs.

Use it to screen applicants in a chat, build a recruiting agent, enrich an ATS, or prototype HR tech features without writing integration code.

Quick start

1. Add the server URL https://hirelayer.co/mcp in your AI app, or click a one-click install button above.
2. Sign in to HireLayer when your app asks, and allow access. No account yet? Sign up for free: 50 credits a month, no card required.
3. Ask your assistant. For example: attach a resume and ask "Summarize this candidate."

Shortened. The full README is on GitHub.