Rezmatch.ai — Resume Parsing & Candidate Matching API<br>Get API key
svg]:pointer-events-none [&>svg]:size-3! [a]:hover:bg-muted [a]:hover:text-muted-foreground mb-6 gap-2 rounded-full border-violet-400/40 bg-violet-500/10 px-4 py-1.5 text-[13px] font-normal text-violet-700 dark:border-violet-400/30 dark:text-violet-200">REST API · MCP server · Agent Skills<br>Parse any résumé.<br>Match any role.<br>The parse-and-match API for hiring products. Résumés and job descriptions in — clean JSON and calibrated, explainable fit scores out. Résumés are never stored.<br>Start free — 100 creditsRead the docs<br>No credit card. First call in under five minutes.
rezmatch — one call, structured candidate<br>$ ▍
Built for the products that hire<br>Applicant tracking systemsJob boardsStaffing platformsSourcing toolsRecruiting agentsHR analyticsTalent marketplacesScreening copilotsApplicant tracking systemsJob boardsStaffing platformsSourcing toolsRecruiting agentsHR analyticsTalent marketplacesScreening copilots
Step 1 — ingest<br>Start with any résumé<br>PDF, raw text, or a URL. Any industry, any format — nurses and accountants, not just engineers.
Step 2 — parse<br>Out comes clean, normalized JSON<br>E.164 phones, canonical titles and employers, computed tenures, taxonomy-pinned skills.
Step 3 — match<br>Scored against the role, with receipts<br>Hard requirements gate the score. Every point is explained — evidence, never verdicts.
PDF<br>priya_sharma.pdf<br>128 KB
candidate.json<br>"name": "Priya Sharma"<br>"phone": "+15125550100"<br>"seniority": "senior"<br>"experience": 103 // months, computed<br>"skills": ["Go", "Kubernetes", "PostgreSQL"]<br>"redacted": ["name", "age_proxies", "gender_proxies"]
role.json<br>Senior Backend Engineer<br>Go · 3y+KubernetesPostgreSQL
strong
✓ Go — 5.4 yrs verified✓ Kubernetes○ Kafka — nice-to-have, missed
Why Rezmatch.ai<br>The matcher is the product<br>Anyone can cosine-similarity two documents. Calibrated scores that hiring teams can defend — that's the hard part, and it's the part we obsess over.
Parsing that survives real résumés<br>Any industry, any formatting — nurses and accountants, not just engineers. E.164 phones, canonical employers and titles, computed tenures, taxonomy-pinned skills.
Scores with receipts<br>Met and missed requirements with evidence, and hard gates that similarity can't sweet-talk: a missing must-have caps the score, period.
Fair by architecture<br>Every requirement verdict is grounded in quoted résumé evidence, and automated parity tests verify that name, age and ethnicity signals never move a score.
Nothing to breach<br>Documents are deleted the moment your response is produced. No candidate database, no retention, no liability surface.
Developers<br>One request.<br>Both documents. A defensible score.<br>Every endpoint takes text, url, or file — job-board URLs fetch directly, PDFs parse natively. Uniform envelope, stable error codes, failures refunded.<br>✓OpenAPI 3.0 spec + interactive playground<br>✓Parse once, match many — reuse candidate JSON across a whole pool<br>✓Free normalize endpoints to smoke-test your integration
curlnodepythonresponse<br>curl -X POST https://api.rezmatch.ai/match \<br>-H "x-access-key: $REZMATCH_API_KEY" \<br>-H "Content-Type: application/json" \<br>-d '{<br>"resume_url": "https://files.acme.dev/resume.pdf",<br>"jd_url": "https://job-boards.greenhouse.io/acme/jobs/123456"<br>}'
Add to Claude — one URL, zero keys<br>https://mcp.rezmatch.ai<br>→Paste as a custom connector, sign in, done. Tool calls meter against your normal balance.<br>parse_resumeparse_jdmatch_candidate_rolescore_requirementsextract_skillsredact_textnormalize_titlenormalize_skill
Built for the agent era<br>Your recruiting agent already knows how to use it<br>A hosted MCP server with OAuth connect, plus an Agent Skills pack for coding agents. The fairness rules ship inside both — an agent using Rezmatch.ai can't skip the parity-tested scoring path or turn scores into verdicts.<br>REST, MCP, and Skills are one surface: same credits, same limits, same explanations. No agent-only pricing games.
Pricing<br>Credits, not seats<br>A full screening — parse a résumé, match it against a role — is 8 credits. Failed calls are refunded. Per-credit price falls as tiers rise, and paid tiers accept larger documents at higher rate limits.
Free<br>$0/mo<br>100 starter credits<br>~11 screenings<br>60 requests/min<br>Résumés up to 2 pages<br>Kick the tires on real documents.
Start free
Starter<br>$19.99/mo<br>400 credits / mo<br>~44 screenings<br>120 requests/min<br>Résumés up to 10 pages<br>First production integration.
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PopularGrowth<br>$79.99/mo<br>1,800 credits / mo<br>~200 screenings<br>300 requests/min<br>Résumés up to 10 pages<br>Steady screening volume.
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Scale<br>$399.99/mo<br>10,000 credits / mo<br>~1,110 screenings<br>600 requests/min<br>Résumés up to 10 pages<br>High-volume pipelines.
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Enterprise<br>Custom<br>Custom volume<br>SLA & invoicing<br>Custom limits<br>Custom document sizes<br>Tailored to your pipeline.
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