# Mercor

**Canonical:** https://apis.io/providers/mercor/  
**Website:** https://www.mercor.com  
**APIs profiled:** 7

Mercor is an AI-powered talent and human-intelligence marketplace that organizes expert humans to power frontier AI work. The platform routes specialized professionals (software engineers, finance and investment-banking experts, clinicians, attorneys, generalist consultants) to AI labs and enterprises for RLHF data, SFT data, agent training, evals, frontier research, and managed data pipelines. Mercor also ships APEX, a public research and benchmarking suite — APEX Benchmarks (AI Productivity Index), APEX-Agents Leaderboard, and APEX-SWE Leaderboard. Mercor maintains documentation hubs at mercor.com/docs and talent.docs.mercor.com (the expert-facing help center), and exposes a developer-facing documentation surface at mercor.com/docs/api. Public API endpoint details are not advertised on the open web at this time; this profile documents the product and documentation surfaces rather than endpoint shapes.

## Kin Score — 25.4 / 100 (emerging)

Scored 2026-08-25 under rubric 0.14.0. Trend: flat (+0.0 from 25.4).

| Facet | Score |
|---|---|
| Discoverability | 72.2 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 23.7 |
| Developer Ergonomics | 33.3 |
| Commercial Clarity | 42.1 |
| Access Clarity | 42.1 |

## Agent readiness — 2.5 (human-only)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| Reversibility Documented | no |
| MCP Server | no |
| Auth Clarity | no |
| Idempotency | no |
| Error Semantics | no |
| OpenAPI Examples | no |
| Rate Limit Signal | documented |
| Event Surface Described | no |
| Agent Skills | no |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |
| Delegated Identity | no |
| Protected Resource Metadata | no |
| Dynamic Client Registration | no |
| Agentic Commerce | no |

## Access

Free — onboarding: unknown, pricing: free, trial: no (confidence: medium).

## APIs (7)

- **Mercor Talent Marketplace** — The core Mercor platform that matches expert humans to AI lab and enterprise demand for RLHF, SFT, evals, agent training, and frontier research projects. Domains covered include...
- **Mercor Data Pipelines** — Mercor's managed data-pipeline product for designing and operating large, expert-driven labeling and evaluation pipelines for AI training data.
- **Mercor API** — Mercor's developer-facing API documentation surface. Endpoint shapes and authentication details are not currently published openly; access is via Mercor's enterprise sales process.
- **APEX Benchmarks (AI Productivity Index)** — Mercor's public AI productivity benchmark and research surface. APEX measures how well AI models perform real expert-grade work.
- **APEX-Agents Leaderboard** — Public leaderboard for AI agent performance run by Mercor's research team.
- **APEX-SWE Leaderboard** — Public leaderboard for AI software-engineering performance run by Mercor's research team.
- **Terminal-Bench** — Public benchmark / task-submission framework published by Mercor (terminal-bench-3 on GitHub) for evaluating AI agents on terminal-based engineering tasks.

## Security (1)

- **Mercor Domain Security** — TLSv1.3 · HSTS · DMARC

## Plans (1)

- **Mercor Plans Pricing**

## Use cases (4)

- **Frontier Model RLHF** — Source preference and reward data from domain experts for RLHF.
- **Expert SFT Data** — Capture demonstrations of expert workflows for supervised fine-tuning.
- **AI Agent Evaluation** — Benchmark agent performance against expert-graded tasks via APEX and Terminal-Bench.
- **Enterprise Data Engineering** — Stand up managed labeling and evaluation pipelines for enterprise AI programs.

## Tags

Talent Marketplace, Human Intelligence, RLHF, SFT, AI Evals, Data Pipeline, APEX Benchmarks

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Profiled by [API Evangelist](https://apievangelist.com) and published on [APIs.io](https://apis.io/providers/mercor/). Scores are computed from the provider's own public artifacts under a published rubric.