HireLayer

co.hirelayerv1.0.0更新於 Oct 6, 2026

Resume and CV parsing, candidate matching and ranking for recruiting and ATS AI agents.

已驗證STDIO僅桌面AI & MLBusiness & Commerce

概覽

AI 產生的概覽

讓助理解析履歷與 CV、把職缺描述轉成篩選條件,並為應徵者評分或排名,用於招募流程。

功能
HireLayer 提供工具,把履歷與 CV 檔案解析成結構化 JSON(聯絡方式、工作經歷、學歷、語言、技能與全文),掃描檔會走 OCR,並偵測履歷語言。它能把職缺描述轉成帶權重與必備條件標記的條件,以 0 到 1 為單一應徵者評分並逐項說明,一次呼叫最多為 10 位應徵者排名,還能把自由文字技能對應到技能分類體系。此外也提供篩選、履歷摘要與技能正規化等提示詞。
適用情境
適合在對話中篩選應徵者、打造招募代理、為 ATS 補充能力,或在不寫整合程式碼的情況下原型驗證 HR 技術功能。對象是招募人員、用人主管,以及想直接使用解析、媒合與排名能力的開發者。
執行需求
透過 npx 以 stdio 在本機執行,需要 Node.js 20 或更新版本。必須在 HIRELAYER_API_KEY 環境變數中提供 HireLayer API 金鑰;免費方案每月 50 個額度。需要透過網路以 HTTPS 存取 HireLayer API。選用變數 HIRELAYER_BASE_URL 可指向測試端點。
安裝前請注意
履歷屬於個人資料,會傳送到 HireLayer API;預設會保存原始檔案並回傳連結,需在呼叫中設定 do_not_store_data: true 才不保存。每次成功呼叫消耗 1 個 HireLayer 額度,回傳 403 表示當月額度已用完。結果文字為法文,由助理翻譯。評分用來輔助而非取代人工招募決策。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 HireLayer,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

[HireLayer logo]

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 version] [CI] [License: MIT] [MCP]

[Install in Cursor] [Install in VS Code] [Install in VS Code Insiders] [Add 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

  • 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
bash
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:

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):

json
{  "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:

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:

json
{  "mcpServers": {    "hirelayer": {      "command": "npx",      "args": ["-y", "hirelayer-mcp"],      "env": { "HIRELAYER_API_KEY": "your-api-key" }    }  }}
OpenAI Codex CLI
bash
codex mcp add hirelayer --env HIRELAYER_API_KEY=your-api-key -- npx -y hirelayer-mcp
Gemini CLI
bash
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
bash
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

ToolWhat it doesTypical input
parse_resumeParses a resume or CV file into structured JSON: contact details, experience, education, languages, skills and the full textA 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_criteriaTurns a job description into weighted criteria: a weight from 1 to 3, a mandatory flag and a rationale for eachJob description text
match_candidateScores one candidate against a job from 0 to 1, with a summary and a status and explanation for each criterionJob text, resume text and criteria
rank_candidatesRanks up to 10 candidates for one job, with a score and a rationale for eachJob text and up to 10 resume texts
resolve_skillsMaps free-text skills in French or English to taxonomy skills, with their families and domainsFree 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:

PromptWhat it does
screen_candidatesRuns the full screening workflow (criteria, parsing, matching) and writes a shortlist
summarize_resumeParses one resume and writes a recruiter summary
normalize_skillsNormalizes a skills section and groups it by domain

How screening works

mermaid
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
json
{  "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.

PlanCreditsPrice
Free50 a monthFree, no card required
Paid plansMore credits and higher limitsSee 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

VariableRequiredDefaultDescription
HIRELAYER_API_KEYYesYour HireLayer API key
HIRELAYER_BASE_URLNohttps://hirelayer.coAPI base URL, for testing

Troubleshooting

SymptomFix
HIRELAYER_API_KEY is not setAdd the env block with your key to the client config, then restart the client.
HireLayer API returned 401The key is wrong or revoked. Copy it again from Dashboard → API keys.
HireLayer API returned 403You have used your monthly credits. Wait for the reset or upgrade your plan.
Parsing seems slowParsing 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.jsInstall Node.js 20 or later from nodejs.org.
The file is not foundUse an absolute path, for example /Users/me/Downloads/cv.pdf rather than ~/Downloads/cv.pdf.

To debug, run the server in the MCP Inspector:

bash
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

bash
git clone https://github.com/hirelayer/hirelayer-mcp.gitcd hirelayer-mcpnpm installnpm testHIRELAYER_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

來源:README.md,提交 779d087

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版本歷史

1
  1. v1.0.0最新Oct 6, 2026