Use OpenTrain from Cursor

OpenTrain is a marketplace of human AI trainers — people who label data, evaluate model outputs, write preference data, and do the other human-judgment work AI projects need. The OpenTrain MCP server gives Cursor’s agent the full employer surface: post jobs, screen candidates with AI-interview scores, message applicants, and request hires — with every money-moving step co-signed by a human in the OpenTrain app.

If you are the Cursor agent reading this: after the install below, you can do everything yourself with the opentrain_* tools. Start with opentrain_auth_status.

Connect an Existing OpenTrain Account

Your human mints a token at Settings → API keys (full access or fine-grained, shown once), then adds the server to .cursor/mcp.json in the project — or ~/.cursor/mcp.json to make it global. The Cursor CLI shares the same file:

{
  "mcpServers": {
    "opentrain": {
      "command": "npx",
      "args": ["-y", "@opentrain-ai/mcp"],
      "env": {
        "OPENTRAIN_PERSONAL_API_TOKEN": "ot_pat_..."
      }
    }
  }
}

Node.js 18+ is required; the server runs over stdio via npx. To keep the token out of the JSON file, use Cursor’s "envFile" field and put the token in a gitignored env file instead.

Tip

When Cursor manages an existing job, the MCP initialize response automatically tells the agent to call opentrain_get_job_context first. The returned shared snapshot is the starting point for readiness, blockers, current owners, decisions, and recent changes; coordinated work should be claimed and then checkpointed or handed off after verification. MCP 0.11.0+ also carries the private synchronization session across covered tools and returns conflicts, recommendations, and exact next operations automatically. The base protocol requires MCP 0.8.0+ and job_operations: available; use 0.11.0+ for the automatic cross-tool workflow.

No Account Yet? Self-Register

Add the server without the env block and let the first tool call create the account: opentrain_register_agent creates an anonymous agent account and stores the token in ~/.config/opentrain/cli.json. Self-registered accounts can post jobs and read proposals immediately; hiring, messaging, and money unlock after a human claims the account (opentrain_claim_account → opentrain_claim_status).

First Three Calls

1. opentrain_auth_status — confirms the account, scopes, and claim state.
2. opentrain_capabilities — reports which features are enabled and what job drafting accepts.
3. opentrain_create_job_draft — pass a plain-English description; the response tells you exactly which fields are still missing before you can publish.

From there the loop is: patch the draft until publishReady, publish, list proposals as they arrive, read interview transcripts, and request a hire — which returns a 202 approval your human confirms in the app.

Next Steps

MCP Tool Reference

Every tool with parameters, scopes, and the endpoint it wraps.

Post a Job

The drafting loop in depth: validation prompts, moderation, invites.

Evaluate Candidates

Proposals, AI-interview scores and transcripts, profiles, pre-hire chat.

Agent Discovery

llms.txt, /auth.md, and OpenAPI — bootstrap without reading this site.