aid: mercor
name: Mercor
description: 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.
type: Index
image: https://kinlane-productions.s3.amazonaws.com/apis-json/apis-json-logo.jpg
tags:
- Talent Marketplace
- Human Intelligence
- RLHF
- SFT
- AI Evals
- Data Pipelines
- APEX Benchmarks
url: https://raw.githubusercontent.com/api-evangelist/mercor/refs/heads/main/apis.yml
created: '2026-05-23'
modified: '2026-05-23'
specificationVersion: '0.19'
apis:
- aid: mercor:mercor-platform
  name: Mercor Talent Marketplace
  description: 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 software engineering, finance and investment banking,
    healthcare and clinical, legal, and generalist consulting.
  humanURL: https://www.mercor.com
  tags:
  - Talent Marketplace
  - Human Intelligence
  - AI Training Data
  properties:
  - type: Documentation
    url: https://www.mercor.com/docs
  - type: GettingStarted
    url: https://talent.docs.mercor.com/working/getting-started
- aid: mercor:mercor-data-pipelines
  name: Mercor Data Pipelines
  description: Mercor's managed data-pipeline product for designing and operating large, expert-driven labeling and evaluation
    pipelines for AI training data.
  humanURL: https://www.mercor.com/docs/designing-a-data-pipeline/
  tags:
  - Data Pipelines
  - Labeling
  - Managed Service
  properties:
  - type: Documentation
    url: https://www.mercor.com/docs/designing-a-data-pipeline/
- aid: mercor:mercor-api
  name: Mercor API
  description: 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.
  humanURL: https://www.mercor.com/docs/api/
  tags:
  - API
  - Enterprise
  properties:
  - type: Documentation
    url: https://www.mercor.com/docs/api/
- aid: mercor:apex-benchmarks
  name: APEX Benchmarks (AI Productivity Index)
  description: Mercor's public AI productivity benchmark and research surface. APEX measures how well AI models perform real
    expert-grade work.
  humanURL: https://www.mercor.com
  tags:
  - Benchmarks
  - Research
  - Evals
  properties:
  - type: Documentation
    url: https://www.mercor.com
- aid: mercor:apex-agents-leaderboard
  name: APEX-Agents Leaderboard
  description: Public leaderboard for AI agent performance run by Mercor's research team.
  humanURL: https://www.mercor.com
  tags:
  - Leaderboard
  - Agents
  - Evals
  properties:
  - type: Documentation
    url: https://www.mercor.com
- aid: mercor:apex-swe-leaderboard
  name: APEX-SWE Leaderboard
  description: Public leaderboard for AI software-engineering performance run by Mercor's research team.
  humanURL: https://www.mercor.com
  tags:
  - Leaderboard
  - Software Engineering
  - Evals
  properties:
  - type: Documentation
    url: https://www.mercor.com
- aid: mercor:terminal-bench
  name: Terminal-Bench
  description: Public benchmark / task-submission framework published by Mercor (terminal-bench-3 on GitHub) for evaluating
    AI agents on terminal-based engineering tasks.
  humanURL: https://github.com/Mercor-io/terminal-bench-3
  tags:
  - Benchmarks
  - Agents
  - Open Source
  properties:
  - type: GitHubRepository
    url: https://github.com/Mercor-io/terminal-bench-3
common:
- type: Portal
  url: https://www.mercor.com
- type: Documentation
  url: https://www.mercor.com/docs
- type: Documentation
  url: https://talent.docs.mercor.com
  name: Mercor Talent Help Center
- type: APIReference
  url: https://www.mercor.com/docs/api/
- type: Blog
  url: https://www.mercor.com/blog
- type: Careers
  url: https://www.mercor.com/careers/
- type: GitHubOrganization
  url: https://github.com/Mercor-io
- type: SignUp
  url: https://www.mercor.com/experts/
  name: Expert Sign-Up
- type: Support
  url: https://talent.docs.mercor.com/working/getting-started
- type: X
  url: https://x.com/Mercor_ai
- type: Features
  data:
  - name: AI Talent Marketplace
    description: Routes expert humans across software engineering, finance, healthcare, legal, and consulting into AI lab
      and enterprise projects.
  - name: RLHF and SFT Data
    description: Provides preference, reward, and demonstration data for foundation-model training.
  - name: Agent Training Data
    description: Specialist data for training and evaluating AI agents.
  - name: Managed Data Pipelines
    description: End-to-end design and operation of expert-driven labeling and evaluation pipelines.
  - name: APEX Research Suite
    description: Public benchmarks (AI Productivity Index, APEX-Agents, APEX-SWE) measuring real-world AI performance.
  - name: Terminal-Bench
    description: Open-source benchmark and task-submission framework for AI agents on terminal engineering tasks.
- type: UseCases
  data:
  - name: Frontier Model RLHF
    description: Source preference and reward data from domain experts for RLHF.
  - name: Expert SFT Data
    description: Capture demonstrations of expert workflows for supervised fine-tuning.
  - name: AI Agent Evaluation
    description: Benchmark agent performance against expert-graded tasks via APEX and Terminal-Bench.
  - name: Enterprise Data Engineering
    description: Stand up managed labeling and evaluation pipelines for enterprise AI programs.
- type: Integrations
  data:
  - name: Slack
    description: Expert workflows and team coordination run over Slack channels.
  - name: GitHub
    description: Engineering experts integrate with customer GitHub repositories for code-related work.
  - name: Custom Data Pipelines
    description: Mercor designs custom ingest and delivery pipelines per customer engagement.
- type: LLMsTxt
  url: https://talent.docs.mercor.com/llms.txt
maintainers:
- FN: Kin Lane
  url: http://apievangelist.com
  email: kin@apievangelist.com