{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"awesome-career-site-jobs","slug":"career-site-jobs","name":"Career Site Jobs","type":"mcp","url":"https://apify.com/fantastic-jobs/career-site-job-listing-api/api/mcp","page_url":"https://unfragile.ai/career-site-jobs","categories":["mcp-servers"],"tags":[],"pricing":{"model":"unknown","free":false,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"awesome-career-site-jobs__cap_0","uri":"capability://tool.use.integration.multi.ats.job.listing.aggregation.and.retrieval","name":"multi-ats job listing aggregation and retrieval","description":"Aggregates job listings from 175,000+ company career sites across 54 different ATS platforms (Workday, Greenhouse, Ashby, Lever, Rippling, SuccessFactors, iCIMS, ADP, and others) through a unified MCP interface. The system crawls and normalizes job data from heterogeneous ATS sources into a standardized schema, enabling single-query access to jobs regardless of underlying platform. Implements platform-specific parsing logic to extract job details from each ATS's unique HTML/API structure and reconciles data formats into consistent output fields.","intents":["Query jobs from multiple company career sites without building separate integrations for each ATS platform","Access job listings from companies using different ATS systems through a single API endpoint","Retrieve normalized job data across diverse ATS platforms without handling platform-specific parsing logic","Build job aggregation tools that work across the entire ecosystem of company career sites"],"best_for":["Job aggregation platforms and job boards needing multi-source coverage","Recruitment automation tools requiring broad ATS compatibility","Developers building talent marketplace applications","Teams migrating from REST APIs to MCP-based job data access"],"limitations":["Data freshness not guaranteed — update frequency for job listings not specified in documentation","Coverage limited to 175k+ indexed career sites; private or non-indexed company sites not accessible","No real-time job posting guarantees; crawl-based approach introduces latency between job publication and availability","ATS platform support limited to 54 documented platforms; custom or niche ATS systems may not be covered","Pricing model ($4.00 per 1,000 jobs) means high-volume aggregation can become expensive at scale"],"requires":["Apify account with active API key for authentication","MCP client compatible with Model Context Protocol specification","Network access to Apify MCP endpoint (https://apify.com/fantastic-jobs/career-site-job-listing-api/api/mcp)","Sufficient Apify compute units or pay-as-you-go credits ($0.13-$0.20 per compute unit)"],"input_types":["structured query parameters (company name, job title, location filters)","ATS platform filter (optional, to restrict to specific platforms)","pagination parameters (offset, limit)"],"output_types":["structured job listing objects with up to 60 fields per job","normalized job metadata (title, description, location, salary, requirements, application URL)","enriched company data (LinkedIn company information, company size, industry)"],"categories":["tool-use-integration","data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-career-site-jobs__cap_1","uri":"capability://data.processing.analysis.ai.enriched.job.data.normalization.and.enhancement","name":"ai-enriched job data normalization and enhancement","description":"Applies AI-driven enrichment to raw job listings scraped from diverse ATS platforms, standardizing unstructured job descriptions into consistent, queryable fields and augmenting data with derived insights. The enrichment pipeline processes job titles, descriptions, and requirements through NLP models to extract structured metadata (required skills, experience level, job category, salary ranges where not explicitly provided) and reconciles formatting inconsistencies across different ATS platforms. Integrates LinkedIn company data enrichment to add organizational context (company size, industry, growth stage) to each job listing.","intents":["Extract structured job requirements and skills from unstructured job descriptions","Standardize job data across different ATS platforms that use inconsistent formatting","Enrich job listings with company context and industry information without separate company data lookups","Enable filtering and matching on derived fields (required skills, experience level) not explicitly provided by all ATS systems"],"best_for":["Job matching and recommendation engines requiring structured skill extraction","Talent acquisition platforms needing consistent job data across multiple ATS sources","Career development tools that analyze job market trends and skill requirements","Resume-to-job matching systems that need normalized job requirements"],"limitations":["AI enrichment quality depends on job description clarity; sparse or poorly-written descriptions may produce incomplete extractions","Enrichment adds processing latency beyond raw job retrieval; specific latency not documented","Derived fields (skills, experience level) are AI-inferred and may not match recruiter intent in all cases","No control over enrichment model version or retraining frequency; updates to enrichment logic not transparent"],"requires":["Apify account with API access to enrichment pipeline","Acceptance of AI-generated data quality (not human-verified for all fields)","Understanding that enriched fields are inferred, not authoritative"],"input_types":["raw job listing data from ATS platforms","job description text","company metadata"],"output_types":["normalized job title and category","extracted required skills and competencies","inferred experience level (entry, mid, senior)","standardized job description format","enriched company data (size, industry, LinkedIn profile)"],"categories":["data-processing-analysis","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-career-site-jobs__cap_2","uri":"capability://tool.use.integration.mcp.native.job.data.access.with.llm.agent.integration","name":"mcp-native job data access with llm agent integration","description":"Exposes job listing retrieval and querying as MCP tools callable directly by LLM agents and AI assistants, enabling natural language job search and analysis without custom API integration code. Implements MCP tool schema definitions for job queries, filtering, and pagination, allowing Claude, other LLMs, and autonomous agents to invoke job retrieval as part of multi-step reasoning workflows. The MCP transport layer (stdio, SSE, or HTTP) handles serialization and context passing between LLM agents and the job data backend, enabling agents to compose job queries with other tools in a unified execution environment.","intents":["Enable LLM agents to search and retrieve jobs using natural language queries","Integrate job data access into multi-tool LLM agent workflows without custom API wrappers","Allow AI assistants to analyze job markets, trends, and opportunities as part of broader reasoning tasks","Build conversational job search interfaces where agents can refine queries and provide recommendations"],"best_for":["LLM agent developers building autonomous recruitment or job search tools","AI assistant builders integrating job data into broader career guidance systems","Teams using Claude or other LLMs with MCP support for job market analysis","Developers migrating from REST API integrations to MCP-based tool ecosystems"],"limitations":["MCP protocol overhead adds latency compared to direct REST API calls; specific latency not documented","LLM context window constraints limit job result set sizes per query (typical LLM context 4k-200k tokens)","Agent reasoning over large job result sets may require pagination and multiple tool invocations","MCP transport type (stdio vs SSE vs HTTP) not specified; transport choice affects deployment architecture","No built-in agent memory or state persistence; agents must manage conversation history externally"],"requires":["MCP-compatible LLM client (Claude with MCP support, or custom MCP client)","Model Context Protocol runtime environment","Network connectivity to Apify MCP endpoint","Understanding of MCP tool schema and agent execution patterns"],"input_types":["natural language job search queries (from LLM agent)","structured MCP tool invocations with parameters","filter specifications (location, job title, company, ATS platform)"],"output_types":["MCP tool results containing job listings","structured job data formatted for LLM consumption","pagination tokens for multi-step agent queries"],"categories":["tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-career-site-jobs__cap_3","uri":"capability://automation.workflow.pay.as.you.go.job.data.consumption.with.apify.compute.unit.billing","name":"pay-as-you-go job data consumption with apify compute unit billing","description":"Implements metered billing model where job retrieval costs $4.00 per 1,000 jobs retrieved, with underlying costs mapped to Apify compute units ($0.13-$0.20 per unit depending on plan). Billing is integrated with Apify platform account, enabling transparent cost tracking and budget management through Apify's usage dashboard. The pricing model incentivizes efficient queries and result filtering, as each job retrieved incurs cost regardless of whether all fields are consumed by the client.","intents":["Understand and predict costs for job data retrieval at scale","Implement cost-aware job querying logic that minimizes unnecessary retrievals","Budget for job aggregation or recruitment automation projects with transparent per-job pricing","Optimize query efficiency to reduce total job count retrieved and associated costs"],"best_for":["Startups and small teams with variable job data consumption needs","Projects with unpredictable job query volumes that benefit from pay-as-you-go pricing","Cost-conscious developers optimizing job retrieval efficiency","Teams already using Apify platform for other data extraction tasks"],"limitations":["No fixed pricing tier; costs scale linearly with job count, making high-volume aggregation expensive","Pricing ($4.00 per 1,000 jobs) may be prohibitive for large-scale job boards or continuous aggregation","Billing tied to Apify account; no direct payment method or invoice management outside Apify platform","No bulk discounts or volume pricing documented; per-job cost remains constant regardless of scale","Compute unit costs vary by Apify plan ($0.13-$0.20 per unit); exact cost per job depends on plan tier"],"requires":["Active Apify account with payment method on file","Sufficient Apify compute unit balance or active subscription","Access to Apify usage dashboard for cost tracking and billing management"],"input_types":["job query parameters","result set size (number of jobs to retrieve)"],"output_types":["job listing data","usage metrics (jobs retrieved, compute units consumed)","billing information (cost per query)"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-career-site-jobs__cap_4","uri":"capability://automation.workflow.job.listing.feed.alternative.with.streaming.updates","name":"job listing feed alternative with streaming updates","description":"Companion capability provided through the 'Career Site Job Listing Feed' product (4.8★ rating), offering streaming or feed-based access to job updates as an alternative to on-demand query API. The feed model continuously monitors indexed career sites and publishes new job listings, job updates, and job removals as events, enabling subscribers to stay synchronized with job market changes without polling. This architecture suits real-time job board applications and continuous aggregation pipelines that need immediate notification of job changes rather than batch retrieval.","intents":["Receive real-time notifications when new jobs are posted on monitored career sites","Build continuously-updated job boards that reflect current market state without polling","Track job updates and removals across 175k+ career sites with minimal latency","Implement event-driven job aggregation pipelines that react to job market changes"],"best_for":["Real-time job board and job search applications","Event-driven job aggregation pipelines and data warehouses","Recruitment automation systems requiring immediate job market updates","Job market analysis tools tracking trends and changes in real-time"],"limitations":["Feed-based model requires persistent connection or polling mechanism; not suitable for batch-only use cases","Update latency depends on crawl frequency; specific freshness SLA not documented","Feed subscription may incur additional costs beyond per-job retrieval pricing","Requires handling of duplicate job detection and deduplication logic on client side","Feed format and schema not documented in provided materials"],"requires":["Apify account with feed API access","Feed consumer capable of handling streaming or event-based data","Persistent storage for job state tracking and deduplication"],"input_types":["feed subscription parameters","filter criteria (optional)"],"output_types":["job event stream (new jobs, updates, removals)","job listing data in feed format","event metadata (timestamp, change type)"],"categories":["automation-workflow","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-career-site-jobs__cap_5","uri":"capability://tool.use.integration.platform.specific.job.api.variants.for.targeted.integrations","name":"platform-specific job api variants for targeted integrations","description":"Ecosystem of specialized MCP servers and APIs for individual ATS platforms (Workday Jobs API 5.0★, Greenhouse Jobs API 3.0★, Ashby Jobs API, Lever.co Jobs API, ADP Jobs API) enabling developers to integrate with specific platforms at higher fidelity than the aggregated multi-ATS API. Each platform-specific variant provides native access to platform-specific fields, features, and capabilities without normalization or abstraction, allowing deeper integration with particular ATS systems. Developers can choose between the unified aggregation API for broad coverage or platform-specific APIs for deeper integration with particular systems.","intents":["Integrate deeply with a specific ATS platform (Workday, Greenhouse, etc.) using native platform APIs","Access platform-specific job fields and features not available in the aggregated API","Build ATS-native integrations that leverage platform-specific capabilities and data structures","Migrate from REST API to MCP while maintaining platform-specific integration patterns"],"best_for":["Teams deeply integrated with specific ATS platforms (Workday, Greenhouse, etc.)","Recruitment automation tools targeting particular ATS systems","Enterprise integrations requiring native platform API access","Developers needing platform-specific fields or features not available in aggregated API"],"limitations":["Requires separate integration for each ATS platform; no unified query interface","Platform-specific APIs may have different pricing, rate limits, and data freshness guarantees","Quality and maintenance varies by platform (Workday 5.0★ vs Greenhouse 3.0★ ratings indicate variance)","Switching between platforms requires code changes; no abstraction layer for multi-platform support","Platform-specific APIs may be deprecated or updated independently of aggregated API"],"requires":["Apify account with access to specific platform API","Knowledge of target ATS platform's data model and API patterns","Potential authentication with target ATS platform (if required)"],"input_types":["platform-specific query parameters","platform-native filter criteria"],"output_types":["platform-specific job data structures","native platform fields and metadata"],"categories":["tool-use-integration","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-career-site-jobs__cap_6","uri":"capability://data.processing.analysis.expired.job.tracking.and.removal.detection","name":"expired job tracking and removal detection","description":"Companion 'Expired Jobs API' capability that tracks job listings that have been removed or expired from company career sites, enabling job boards and aggregators to maintain accurate, current job listings by detecting and removing stale postings. The system monitors previously-indexed jobs and detects when they are no longer available on career sites, providing removal events or expired job data that allows clients to clean up their job databases. This capability is essential for maintaining data quality in aggregated job boards where jobs may be removed without explicit notification.","intents":["Detect when jobs have been removed or expired from company career sites","Maintain accurate job board data by removing stale postings automatically","Track job lifecycle (posted, updated, expired) across 175k+ career sites","Analyze job market dynamics by tracking job removal patterns and hiring velocity"],"best_for":["Job boards and aggregators requiring accurate, current job listings","Recruitment analytics platforms tracking job market trends and hiring velocity","Job search applications that need to remove expired postings automatically","Data quality teams maintaining job databases across multiple sources"],"limitations":["Expired job detection depends on crawl frequency; specific detection latency not documented","Jobs may be removed from career sites without notification; detection is passive monitoring","Removal detection may lag actual job removal by hours or days depending on crawl schedule","No real-time job removal notifications; batch detection model introduces latency","Pricing and cost model for expired job tracking not documented separately"],"requires":["Apify account with access to Expired Jobs API","Job database or tracking system to correlate expired jobs against","Removal handling logic to delete or archive expired jobs"],"input_types":["previously-indexed job IDs or URLs","date range for expired job detection"],"output_types":["expired job listings","removal event data","job lifecycle metadata (posted date, removal date)"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":26,"verified":false,"data_access_risk":"high","permissions":["Apify account with active API key for authentication","MCP client compatible with Model Context Protocol specification","Network access to Apify MCP endpoint (https://apify.com/fantastic-jobs/career-site-job-listing-api/api/mcp)","Sufficient Apify compute units or pay-as-you-go credits ($0.13-$0.20 per compute unit)","Apify account with API access to enrichment pipeline","Acceptance of AI-generated data quality (not human-verified for all fields)","Understanding that enriched fields are inferred, not authoritative","MCP-compatible LLM client (Claude with MCP support, or custom MCP client)","Model Context Protocol runtime environment","Network connectivity to Apify MCP endpoint"],"failure_modes":["Data freshness not guaranteed — update frequency for job listings not specified in documentation","Coverage limited to 175k+ indexed career sites; private or non-indexed company sites not accessible","No real-time job posting guarantees; crawl-based approach introduces latency between job publication and availability","ATS platform support limited to 54 documented platforms; custom or niche ATS systems may not be covered","Pricing model ($4.00 per 1,000 jobs) means high-volume aggregation can become expensive at scale","AI enrichment quality depends on job description clarity; sparse or poorly-written descriptions may produce incomplete extractions","Enrichment adds processing latency beyond raw job retrieval; specific latency not documented","Derived fields (skills, experience level) are AI-inferred and may not match recruiter intent in all cases","No control over enrichment model version or retraining frequency; updates to enrichment logic not transparent","MCP protocol overhead adds latency compared to direct REST API calls; specific latency not documented","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.24,"ecosystem":0.25,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-06-17T09:51:02.371Z","last_scraped_at":"2026-05-03T14:00:15.503Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=career-site-jobs","compare_url":"https://unfragile.ai/compare?artifact=career-site-jobs"}},"signature":"NetImoUsiUWa0Mn1bxLocMH24AfSOCOVI5XGb3Kxkjl8N0RJZUg9a+xpb1ju2jKE6VcX2RIPdu8WleZGF0mEBw==","signedAt":"2026-06-20T21:48:09.425Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/career-site-jobs","artifact":"https://unfragile.ai/career-site-jobs","verify":"https://unfragile.ai/api/v1/verify?slug=career-site-jobs","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}