HireLayer

HireLayer MCP Server

Community HireLayer
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Official HireLayer MCP server: resume & CV parsing, job criteria extraction, candidate matching & ranking, and skills normalization for AI agents in Claude, Cursor, VS Code and Codex. Built for recruiting, ATS and HR tech.

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, Cursor, VS Code, Codex or any MCP client.

npm versionCILicense: MITMCP

Install in CursorInstall in VS CodeInstall in VS Code InsidersAdd to LM Studio

"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. Get a free API key. Sign up at hirelayer.co, with no card required, and copy your key from Dashboard → API keys. The free plan includes 50 credits a month.
  2. Add the server to your client. Click a one-click install button above, or copy a config from the next section.
  3. Ask your assistant. For example: "Parse ~/Downloads/resume.pdf and summarize the candidate."

To try it without your own data, use the sample job and resumes in examples/. The repository ships a .mcp.json: clone it, export HIRELAYER_API_KEY, open the folder in Claude Code and it offers to enable the server.

Requires Node.js 20 or later, because the server runs with npx.

Install in your MCP client

Replace your-api-key with your HireLayer API key in each config below.

Claude Code
claude mcp add hirelayer --env HIRELAYER_API_KEY=your-api-key -- npx -y hirelayer-mcp
Claude Desktop

Open Settings → Developer → Edit Config and add the server to claude_desktop_config.json:

{
  "mcpServers": {
    "hirelayer": {
      "command": "npx",
      "args": ["-y", "hirelayer-mcp"],
      "env": { "HIRELAYER_API_KEY": "your-api-key" }
    }
  }
}

Restart Claude Desktop.

Cursor

Click Install in Cursor above, or add this to ~/.cursor/mcp.json (all projects) or .cursor/mcp.json (one project):

{
  "mcpServers": {
    "hirelayer": {
      "command": "npx",
      "args": ["-y", "hirelayer-mcp"],
      "env": { "HIRELAYER_API_KEY": "your-api-key" }
    }
  }
}
VS Code (GitHub Copilot)

Click Install in VS Code above. VS Code asks for your API key and stores it securely. To configure it by hand, add this to .vscode/mcp.json:

{
  "inputs": [
    { "type": "promptString", "id": "hirelayer_api_key", "description": "HireLayer API key", "password": true }
  ],
  "servers": {
    "hirelayer": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "hirelayer-mcp"],
      "env": { "HIRELAYER_API_KEY": "${input:hirelayer_api_key}" }
    }
  }
}
Windsurf

Add this to ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "hirelayer": {
      "command": "npx",
      "args": ["-y", "hirelayer-mcp"],
      "env": { "HIRELAYER_API_KEY": "your-api-key" }
    }
  }
}
OpenAI Codex CLI
codex mcp add hirelayer --env HIRELAYER_API_KEY=your-api-key -- npx -y hirelayer-mcp
Gemini CLI
gemini mcp add -e HIRELAYER_API_KEY=your-api-key hirelayer npx -y hirelayer-mcp
Cline, Roo Code, Zed, LM Studio and other clients

Any client that runs stdio MCP servers works with this command and environment variable:

  • Command: npx -y hirelayer-mcp
  • Environment: HIRELAYER_API_KEY=your-api-key

Cline users can also ask Cline to install the server: llms-install.md has the steps.

Docker
docker build -t hirelayer-mcp .
docker run -i --rm -e HIRELAYER_API_KEY=your-api-key hirelayer-mcp

In Docker, parse_resume only reads files that you mount into the container. Otherwise, pass file_url.

Tools

Tool What it does Typical input
parse_resume Parses a resume or CV file into structured JSON: contact details, experience, education, languages, skills and the full text A local file_path or a public file_url. Accepts PDF, DOC, DOCX, ODT, RTF, TXT, PPT, PPTX, ODP, XLS, JPG, PNG or BMP files under 4.5 MB.
extract_job_criteria Turns a job description into weighted criteria: a weight from 1 to 3, a mandatory flag and a rationale for each Job description text
match_candidate Scores one candidate against a job from 0 to 1, with a summary and a status and explanation for each criterion Job text, resume text and criteria
rank_candidates Ranks up to 10 candidates for one job, with a score and a rationale for each Job text and up to 10 resume texts
resolve_skills Maps free-text skills in French or English to taxonomy skills, with their families and domains Free text, from one skill to a whole skills section

All tools only read and analyse data. They never change anything in your systems.

The server also ships prompts that clients show as ready-made commands:

Prompt What it does
screen_candidates Runs the full screening workflow (criteria, parsing, matching) and writes a shortlist
summarize_resume Parses one resume and writes a recruiter summary
normalize_skills Normalizes a skills section and groups it by domain

How screening works

flowchart LR
    J[Job description] --> C[extract_job_criteria]
    R[Resume files] --> P[parse_resume]
    C --> M[match_candidate]
    P --> M
    P --> K[rank_candidates]
    J --> K
    M --> S[Shortlist with explanations]
    K --> S
Example output from match_candidate
{
  "score": 0.89,
  "summary": "Profil très aligné : React, TypeScript et l’expérience demandée sont démontrés. Le niveau d’anglais reste à confirmer.",
  "evaluated_criteria": [
    {
      "id": "crit_1",
      "label": "Maîtrise de React",
      "weight": 3,
      "is_mandatory": true,
      "match_status": "ideal",
      "match_explanation": "Le CV décrit une équipe React dirigée depuis 2022 sur une plateforme en production."
    }
  ]
}

Criteria labels, rationales, summaries and explanations are written in French. Your assistant translates them when it answers you in another language.

Example prompts

Recruiters and hiring managers

  • "Parse ~/Downloads/jane-doe.pdf and summarize her experience in five bullet points."
  • "Here is our job description for a Senior Data Engineer. Extract the criteria, then tell me which ones are must-haves."
  • "Score the resumes in ~/candidates/ against this job and give me a shortlist table with scores and main gaps."
  • "Rank these 8 candidates for the Account Executive role and explain why the top 3 stand out."
  • "Does this candidate meet every mandatory criterion? If not, which ones are missing?"

Developers and HR tech teams

  • "Parse this resume and map the result to our ATS candidate schema: { name, email, current_title, skills[] }."
  • "Normalize this skills section: Pack Office (Word, Excel), React.js, anglais courant, gestion de projet."
  • "Write a TypeScript function that sends a resume to the HireLayer API, using the JSON this tool returned as the expected type."

Try it now with the sample files

  • "Screen the resumes in examples/ against examples/job-senior-react-developer.md."

Pricing and credits

Each successful tool call costs 1 HireLayer credit. A rank_candidates call costs 1 credit whatever the number of candidates. Failed calls are not charged.

Plan Credits Price
Free 50 a month Free, no card required
Paid plans More credits and higher limits See hirelayer.co/#pricing

Data and privacy

  • The server runs on your machine and calls the HireLayer API over HTTPS with your API key. It has no telemetry.
  • parse_resume reads only the file you name. By default HireLayer stores the original file and returns a link to it in info_resume.url. Set do_not_store_data: true in a call so the file is not stored.
  • See the privacy policy and the security policy.

Resumes contain personal data. Use the tools in line with your hiring process and the rules that apply to you, such as GDPR. Scores support human decisions; they don't replace them.

Configuration

Variable Required Default Description
HIRELAYER_API_KEY Yes Your HireLayer API key
HIRELAYER_BASE_URL No https://hirelayer.co API base URL, for testing

Troubleshooting

Symptom Fix
HIRELAYER_API_KEY is not set Add the env block with your key to the client config, then restart the client.
HireLayer API returned 401 The key is wrong or revoked. Copy it again from Dashboard → API keys.
HireLayer API returned 403 You have used your monthly credits. Wait for the reset or upgrade your plan.
Parsing seems slow Parsing usually takes about 35 seconds, and longer for scans that need OCR. The server sends progress updates so clients don't time out.
npx not found or an old Node.js Install Node.js 20 or later from nodejs.org.
The file is not found Use an absolute path, for example /Users/me/Downloads/cv.pdf rather than ~/Downloads/cv.pdf.

To debug, run the server in the MCP Inspector:

HIRELAYER_API_KEY=your-api-key npx @modelcontextprotocol/inspector npx -y hirelayer-mcp

FAQ

Is HireLayer an ATS?No. HireLayer provides the AI building blocks of recruiting software: resume parsing, matching, ranking and skills. Use them on their own through MCP, or plug them into your ATS or HR tech product through the REST API.

Which language are the results in?The text that HireLayer writes (criteria labels and rationales, match summaries and explanations, ranking rationales) is in French; your assistant translates it when it answers in another language. Skills resolution returns French or English labels.

Which resume languages are supported?The parser detects the main language of each resume and returns it in info_resume.language.

Can I use the REST API directly?Yes. See the API reference, the OpenAPI spec and llms.txt for agents.

Is there a hosted remote server?A hosted server with one-click sign-in (OAuth) is on the way. For now, the server runs locally with npx.

Development

git clone https://github.com/hirelayer/hirelayer-mcp.git
cd hirelayer-mcp
npm install
npm test
HIRELAYER_API_KEY=your-api-key npx @modelcontextprotocol/inspector node dist/index.js

See CONTRIBUTING.md. Report bugs in GitHub issues and vulnerabilities as described in SECURITY.md.

Links

License

MIT

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