Official server for AI agents

Resume parsing and candidate matching MCP server

The HireLayer MCP server lets Claude, ChatGPT, Cursor, VS Code, Codex and any MCP client parse resumes, turn job descriptions into criteria, then score and rank candidates, with an explanation for every result.

Get a free API key View on GitHub

URLhttps://hirelayer.co/mcp

Install in Cursor Install in VS Code

Add the URL in Claude or ChatGPT and sign in: no API key to copy. 50 free credits a month, no card required.

Your AI assistant · hirelayer connectedMCP

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

extract_job_criteria1 job description
parse_resume3 resumes
match_candidate3 candidates

Here is the shortlist, scored criterion by criterion:

Alex MorganStrong match: React, TypeScript, team leadInterview
Camille DurandPartial: senior front end, Vue.js rather than ReactMaybe
Sam LeeWeak: back-end profile with some ReactPass

Fictional sample files from the repository. This run uses about 7 credits: 1 for the criteria, 3 for parsing and 3 for matching.

Server URL: https://hirelayer.co/mcp
Transport: Streamable HTTP, or stdio with npx
Authentication: OAuth sign-in, or API key
Registry: co.hirelayer/hirelayer
Local package: hirelayer-mcp
License: MIT, open source

What you can do

Five recruiting tools for your AI assistant

Screen applicants in a chat, build a recruiting agent, enrich an ATS or prototype HR tech features without writing integration code. Every tool only reads and analyses data: it never changes anything in your systems.

parse_resume
Parse resumes and CVs
Turns a resume file 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.
Input: A local file path or a public file URL. PDF, DOC, DOCX, ODT, RTF, TXT, PPT, PPTX, ODP, XLS, JPG, PNG or BMP, under 4.5 MB.
HireLayer CV Extract API reference
extract_job_criteria
Turn a job description into criteria
Returns weighted matching criteria: a weight from 1 to 3, a mandatory flag and a rationale for each one.
Input: Job description text, in any language.
HireLayer Job Extract API reference
match_candidate
Match a candidate to a job
Scores one resume against a job from 0 to 1, with a summary and a status and explanation for each criterion.
Input: Job text, resume text and the criteria to evaluate.
HireLayer Match API reference
rank_candidates
Rank candidates
Orders up to 10 candidates for the same job in one call, with a rank, a score and a rationale for each.
Input: Job text and up to 10 resume texts.
HireLayer Rank API reference
resolve_skills
Normalize skills
Maps free-text skills in French or English to a skills taxonomy with stable IDs, families and domains.
Input: Free text, from one skill to a whole skills section.
HireLayer Skills API reference
Ready-made prompts
Clients show these as commands you can run in one click.
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.

Quick start

Up and running in three steps

About two minutes from sign-up to your first parsed resume.

STEP 01
Add the server URL
In Claude, ChatGPT, Cursor or VS Code, add a server with the URL https://hirelayer.co/mcp, or use a one-click install below.
STEP 02
Sign in to HireLayer
Your app opens the HireLayer sign-in page: log in or create a free account (50 credits a month, no card) and allow access. No API key to copy.
STEP 03
Ask your assistant
For example: attach a resume and ask “Summarize this candidate.” The assistant picks the right tool and explains the result.

Install

Add HireLayer to your MCP client

Add the server URL, then sign in to HireLayer when your app asks. The local npx server uses an API key instead.

Install in Cursor Install in VS Code

Client

https://hirelayer.co/mcp

https://hirelayer.co/mcp

claude mcp add --transport http hirelayer https://hirelayer.co/mcp

{
  "mcpServers": {
    "hirelayer": { "url": "https://hirelayer.co/mcp" }
  }
}

{
  "servers": {
    "hirelayer": { "type": "http", "url": "https://hirelayer.co/mcp" }
  }
}

codex mcp add hirelayer --url https://hirelayer.co/mcp
codex mcp login hirelayer

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

Where it goes

Claude: Claude (web and desktop): Settings → Connectors → Add custom connector, paste the URL, then Connect and sign in to HireLayer.
ChatGPT: ChatGPT: in Settings → Apps, turn on developer mode, create an app with this URL and OAuth authentication, then sign in to HireLayer.
Claude Code: Run the command, then /mcp in Claude Code to sign in.
Cursor: Use the one-click install, or add the server to ~/.cursor/mcp.json, then click Connect.
VS Code: Use the one-click install, or add this to .vscode/mcp.json. VS Code opens the sign-in page.
Codex CLI: Run both commands; the second one opens the sign-in page.
Local (npx): Any client that runs stdio servers (Claude Desktop, Windsurf, Cline, Zed, LM Studio…): runs on your machine with an API key, and reads local resume files.

To read resume files from your disk, run the server locally with npx -y hirelayer-mcp and the HIRELAYER_API_KEY environment variable.

README and troubleshooting npm package

Example prompts

Ask in plain language

Your assistant chooses the tools, chains them and explains the result.

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.”

No resumes at hand? The repository ships a fictional job and three resumes. Try the sample files.

Screening workflow

How candidate screening works

Ask for a shortlist and the assistant chains the tools for you. The screen_candidates prompt runs the same workflow in one command.

01
Read the job
extract_job_criteria
The job description becomes weighted criteria, with must-haves flagged.
02
Read each resume
parse_resume
Every CV becomes structured JSON and plain text the next tools can score.
03
Score criterion by criterion
match_candidate
Each candidate gets a score from 0 to 1 and an explanation per criterion.
04
Or rank the whole list
rank_candidates
Up to 10 candidates ordered in one call, each with a rationale.

Explained results, not just a number

match_candidate returns a score from 0 to 1, a summary and, for every criterion, its weight, whether it is mandatory, a match status and an explanation drawn from the resume. Use it when you need the detail; use rank_candidates to order a list of up to 10 candidates in one call.

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

Scores support human decisions; they don’t replace them.

match_candidate result (excerpt)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."
    }
  ]
}

Pricing and credits

1 credit per successful tool call

The MCP server is free and open source. Tool calls use the credits of your HireLayer plan, shared with the REST API.

1 successful API call = 1 credit across every API.
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
Starter	500 a month	€24 / month
Scale	2,000 a month	€89 / month
Enterprise	Custom volume	On quote

See plans and credit packs

Data and privacy

Sends only what you ask, under your control

You choose the apps
An app gets access only after you sign in and allow it. Disconnect it any time by revoking its (MCP) key in Dashboard → API keys.
Only the files you send
Resumes reach HireLayer over HTTPS only when a tool is called with them. The local server reads only the file paths you name.
Resume files are not stored
The hosted server never stores resume files. With the local npx server, set do_not_store_data to true to keep the file out of storage.
Humans decide
Resumes contain personal data: use the tools in line with your hiring process and rules such as GDPR.

Read the privacy policy

Questions

HireLayer MCP server FAQ

What is the HireLayer MCP server?

It is the official Model Context Protocol server for HireLayer. It gives AI assistants such as Claude, Cursor, VS Code Copilot and Codex five recruiting tools: resume parsing, job criteria extraction, candidate matching, candidate ranking and skills normalization. It is open source (MIT) and published on npm as hirelayer-mcp.

Which MCP clients does it work with?

Claude (web, desktop and Claude Code), ChatGPT, Cursor, VS Code with GitHub Copilot, Codex and any client that supports remote MCP servers connect to https://hirelayer.co/mcp and sign in with OAuth. Clients that only run local servers use npx -y hirelayer-mcp with an API key.

Do I need to write code?

No. Once the server is added to your client, you ask in plain language and the assistant calls the tools. Developers can use the same tools to prototype an integration, then call the REST API from their own code.

How much does it cost?

Each successful tool call costs 1 HireLayer credit; a rank_candidates call costs 1 credit whatever the number of candidates, and failed calls are not charged. The Free plan includes 50 credits a month with no card required. Paid plans add more credits.

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.

Are my resumes stored?

Resumes are sent to the HireLayer API over HTTPS only when a tool is called. The hosted server never stores resume files; the local npx server stores them only if you ask it to.

Do I need an API key?

No, with the hosted server at https://hirelayer.co/mcp: you sign in to HireLayer and allow access, and the app's calls are billed to your plan. You can disconnect an app at any time by revoking its "(MCP)" key in Dashboard → API keys. The local npx server uses an API key instead.

Can I use the REST API instead?

Yes. The MCP server calls the same public API. For code integrations, call the REST API directly: see the API reference, the OpenAPI document and llms.txt.

HireLayer MCP server

Give your assistant a recruiting toolkit today.

Create a free account, copy your API key and add the server to your client. Building it into your own product? Call the same APIs over REST.

Get a free API key Build with AI agents

Resume parsing and candidate matching MCP server

Five recruiting tools for your AI assistant

Parse resumes and CVs

Turn a job description into criteria

Match a candidate to a job

Rank candidates

Normalize skills

Up and running in three steps

Add the server URL

Sign in to HireLayer

Ask your assistant