OJCP
OJCP (Open Job Context Protocol) is an open standard that defines how AI agents discover, evaluate, and apply to job opportunities via interoperable, privacy-preserving schemas and MCP-native tools, targeted at employers, ATS vendors, job boards, staffing agencies, and agent platforms.
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Quick Overview
Best for: Recruitment & HR
What it does
Recruitment & HR software for decision-makers comparing workflow fit and alternatives.
Best fit
Recruitment & HR
Pricing snapshot
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OJCP (Open Job Context Protocol) is an open community standard that defines how AI agents discover, reason about, and act on job opportunities. It provides a set of MCP-native tools and seven core schemas (including JobPosting, CandidateContext, AgentDeclaration, and Manifest) so that agents and providers can exchange structured, discoverable, and privacy-respecting data.
Built by a coalition of employers, ATS vendors, job boards, staffing agencies, and agent platforms, OJCP is interoperable with schema.org, governed by an independent steering committee, and designed to compose with the broader agentic web. The project publishes a draft specification, JSON schemas, examples, and a live playground demonstrating provider endpoints and MCP tool calls.
The open standard for agent-consumable job feeds. Discover, reason over, and act on job opportunities with AI agents.
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Claim this listing for $29Key Features
MCP-native Tools
Defines six standard MCP tools (search_jobs required, get_job_detail, get_employer_context, begin_applications, submit_application, check_application_status) so MCP clients can call job-capability tools out of the box.
Structured Discovery (Manifest)
Providers expose a manifest at /.well-known/ojcp.json that declares available tools, apply paths, MCP endpoint, auth requirements, and rate limits for automatic agent discovery.
Normalized Apply Paths
Standard taxonomy of application mechanisms (ats_direct, provider_hosted, platform_native, email, external_redirect, custom) so agents understand how to apply and what support to expect.
Consent-First Privacy
Candidate data is opt-in and consent-scoped (CandidateContext schema). Resume embeddings are suggested to enable fit-scoring without transmitting PII, and agents self-declare identity and consent tokens.
Agent-Aware Ranking
search_jobs supports an optional candidate_context for personalized ranking; providers return fit_score and fit_rationale alongside job metadata.
Verification & Proofs
VerificationProof schema requires JWS claims (iss, aud, sub, iat, exp, nonce) and verifier manifests support proof delivery methods, formats, and public key discovery (JWKS).
Web / MCP Ready
Browser-native agents can access OJCP tools via navigator.modelContext and the same MCP schemas and tools, enabling new browser surfaces.
Pricing
OJCP is an open community specification; spec content licensed CC BY 4.0 and reference code under Apache 2.0 (no commercial pricing published).
Use Cases
Job Board & ATS Integration
Expose job feeds and apply paths via the OJCP manifest so agent clients and third-party platforms can discover and interact with listings programmatically.
Agent-Powered Job Search
AI agents call search_jobs with CandidateContext to provide personalized, fit-scored job recommendations using fit_score and fit_rationale returned by providers.
Standardized Automated Applications
Agents begin and submit applications using begin_application and submit_application flows with agent_declaration and candidate consent tokens for consistent automated apply experiences.
Verification & Audit Trails
Use verification-step and verification-proof schemas plus verifier manifests to surface human-required identity verification steps and JWS-based proofs for auditability.
Integrations
MCP (Model Context Protocol)
OJCP tools are valid MCP tools and any MCP client can call search_jobs, get_job_detail, and begin_application.
schema.org (JobPosting)
JobPosting schema extends schema.org/JobPosting with agent-specific fields so providers stay compatible with existing web schemas.
ATS platforms (e.g., Workday, Greenhouse, Lever)
Apply path taxonomy includes ats_direct for direct ATS integrations (Workday, Greenhouse, Lever, etc.).
Browser agent APIs (navigator.modelContext)
WebMCP readiness allows browser-native agents to access OJCP tools via navigator.modelContext.
Benefits
Limitations
Frequently Asked Questions
No verified FAQs are available.
Getting Started
- 1 Read the OJCP v0.1 specification and JSON schemas on the official site.
- 2 View the reference implementation and repository on GitHub (links available from the site) and open issues or contribute.
- 3 Expose a provider manifest at /.well-known/ojcp.json declaring your mcp_endpoint, tools, apply_paths, auth, and rate_limits.
- 4 Implement the required MCP tool search_jobs (other tools are recommended) and support apply_paths appropriate for your platform.
- 5 Test integrations using the Live Playground which provides mock provider endpoints and MCP tool calls.
Support
Documentation
Specification, schemas, and examples on the official site (Read the Spec, Explore Schemas).
GitHub / Issues
Repository, issue tracker, and code contributions via the project's GitHub (links available on site).
Community / Discussions
Open calls to 'Join the Discussion', 'Get Involved', and community steering; community channels and contribution guides on the site.
API
https://ojcp.dev/
Provider manifests can declare rate limits (example manifest includes anonymous_rps: 10, authenticated_rps: 50, burst_limit: 100); actual limits specified per-provider in /.well-known/ojcp.json.
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