OJCP – an open protocol for agent-consumable job data
Author here! Agents are applying to jobs for people right now, with progressively more volume, and there's nothing built for it. So they scrape career pages and fight ATS forms with Playwright/Browser Use, which breaks constantly (or they get bot blocked). Employers get buried in applications that don't fit, candidates hear nothing back, and the resume is now an AI-written thing that another AI scores (which breaks the existing model entirely, btw). OJCP is MCP tools for search and apply, a manifest at /.well-known/ojcp.json so agents can find providers, and schemas that…
In plain words
OJCP is an open protocol that enables AI agents to discover, search, and apply for jobs through a standardized interface. Built on the Model Context Protocol, it provides structured job data and application tools that work across job boards, career pages, and ATS systems without requiring web scraping or browser automation. The protocol is governed by representatives from employers, job boards, ATS vendors, and agent platforms, designed to reduce application spam, improve candidate communication, and create a reliable way for agents to interact with job opportunities.
written from the facts on this page · September 2026
From the sources
The open standard for agent-consumable job feeds. Discover, reason over, and act on job opportunities with AI agents.
OJCP defines how AI agents discover, reason over, and act on job opportunities. Built on MCP. Interoperable with schema.org. Governed by an independent steering committee , and designed to compose with the broader agentic web. OJCP is shaped by employers, ATS vendors, job boards, staffing agencies, and agent platforms — each holding one seat, none holding a veto. A shared protocol so AI agents and job providers speak the same language — structured, discoverable, privacy-respecting. OJCP tools are valid MCP tools. Any MCP client can call search_jobs, get_job_detail, and begin_application out of the box. Providers expose a manifest at /.well-known/ojcp.json. Agents discover capabilities,…from ojcp.dev
In the maker’s words, at launch
Author here! Agents are applying to jobs for people right now, with progressively more volume, and there's nothing built for it. So they scrape career pages and fight ATS forms with Playwright/Browser Use, which breaks constantly (or they get bot blocked). Employers get buried in applications that don't fit, candidates hear nothing back, and the resume is now an AI-written thing that another AI scores (which breaks the existing model entirely, btw). OJCP is MCP tools for search and apply, a manifest at /.well-known/ojcp.json so agents can find providers, and schemas that extend schema.org instead of replacing it. The playground on the site is a live MCP endpoint, so you can throw calls at it right now. Why a spec at all when models keep getting better at figuring things out? Inference can't produce authorization. An agent can work out what a form wants. It can't establish that someone consented to this specific submission, and then employer has no way to verify who's calling. So TL;DR a more capable agent is also a more capable impersonator. In this model, trust runs both direction. Agents sign requests using the same method that CloudFlare and OpenAI are already using, providers sign their manifests, agents can check against a JWKS, and trust tiers cap how much candidate PII can go to a given provider. Validation happens at consent, so browsing costs nothing and you only pay the verify when the interaction occurs. I'm the CTO of Recruitics (job advertising) and spent time at LinkedIn before that, so I've been at the intersection of hiring and job search for a while and have felt the pain of both sides. Happy to answer any questions!
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