AI Resilience API & MCP

Free, public API for AI career resilience data. No API key required. Rate limited to 100 requests per minute per IP.

Single-Career Endpoint

Path Parameter

Query Parameters

All parameters are optional. area and county are mutually exclusive.

Response Format

Success (200)

Fields are grouped by concern. All numeric scores are on a 0-1 scale unless otherwise noted. Any field can be null when the underlying data is unavailable for that occupation.

Every successful response also carries a top-level attribution object (required, text, url, license, sources) so you can render the required credit directly from the payload. See Attribution.

Core

aiResilience

airm_cv (AI Resilience Model, CareerVillage)

sources

Per-source signals that feed the combined resilience score. Percentiles are 0-1 within their respective populations.

subscores

stepsToTake

tasks

Populated for detailed occupations only. Sorted by automationLikelihood ascending (most resilient first).

expertise (Experience Outlook — added in v1.1)

Career-level expertise shift derived from the per-task tasks[].expertiseLevel and tasks[].automationLikelihood scores — the same math behind the site's Experience Outlook panel.

expertise.bands

laborMarket

BLS employment and wage data. Employment counts are absolute (not in thousands).

local (Local Picture — added in v1.1)

Metro/nonmetro wage and employment for the occupation, from BLS OEWS. Populated when the request passes ?area= or ?county=. For the full per-area table, use the Local Areas Endpoint.

hierarchy

SOC hierarchy relationships. Each reference is a minimal {code, name, slug, url} object.

Example Response

{
  "success": true,
  "data": {
    "code": "15-1252.00",
    "name": "Software Developers",
    "nameShort": "Software Developers",
    "slug": "software-developers",
    "level": "detailed",
    "description": "Develop, create, and modify general computer applications software...",
    "url": "https://www.airesilience.org/career/software-developers",
    "aiResilience": {
      "score": 0.62,
      "label": "Mostly Resilient",
      "confidence": "High",
      "confidenceScore": 82,
      "explanation": "Software developers..."
    },
    "airm_cv": {
      "version": "v1.5",
      "percentile": 0.45,
      "label": "Medium",
      "rawScore": 0.52
    },
    "sources": {
      "anthropic":      { "percentile": 0.42, "rawScore": 0.18 },
      "microsoft":      { "percentile": 0.38, "rawScore": 0.45 },
      "wrtmj":          { "percentile": 0.55, "label": "Medium", "rawRiskPercent": "65", "growth": "...", "volume": "..." },
      "openai":         { "percentile": 0.47, "rawScore": 0.0038 },
      "althoff":        { "wageBillPercentile": 0.61, "rawScore": 0.74 },
      "manning":        { "adaptiveCapacityPercentile": 0.58, "adaptiveCapacityRawScore": 0.63 },
      "lted_blsOpportunity": { "score": 0.7, "label": "High" }
    },
    "subscores": {
      "meaningfulHumanContribution":  { "score": 0.65, "label": "High" },
      "sustainedEconomicOpportunity": { "score": 0.70, "label": "High" }
    },
    "stepsToTake": [
      "Build a portfolio of projects that show end-to-end problem solving...",
      "Develop fluency with AI-assisted coding tools..."
    ],
    "tasks": [
      {
        "id": "1",
        "task": "Confer with systems analysts, engineers, programmers and others...",
        "taskType": "Core",
        "automationLikelihood": 0.18,
        "resilienceScore": 0.82,
        "expertiseLevel": 0.55,
        "analysisDate": "2026-05-16"
      }
    ],
    "expertise": {
      "deltaExpertise": 0.0215,
      "deltaExpertisePercentile": 79,
      "routine": { "resilience": 0.42, "erosion": 0.55 },
      "expert":  { "resilience": 0.71, "erosion": 0.12 },
      "forecast": {
        "wage":       { "center": 1.8,  "low": 0.9,  "high": 2.7 },
        "employment": { "center": -2.7, "low": -3.4, "high": -2.0 },
        "unit": "percentage points per decade vs the average occupation",
        "capped": false
      },
      "bands": {
        "entry":  { "label": "Entry",  "personalExposure": 0.58, "careerAvgExposure": 0.44, "rungErosion": 0.67, "bandOutlookModifier": -0.043, "sentiment": "negative", "definingTaskCount": 6 },
        "mid":    { "label": "Mid",    "personalExposure": 0.49, "careerAvgExposure": 0.44, "rungErosion": 0.33, "bandOutlookModifier": -0.021, "sentiment": "negative", "definingTaskCount": 6 },
        "senior": { "label": "Senior", "personalExposure": 0.41, "careerAvgExposure": 0.44, "rungErosion": 0.17, "bandOutlookModifier": 0.043,  "sentiment": "positive", "definingTaskCount": 6 }
      },
      "scoredTaskCount": 18,
      "method": "Autor & Thompson (2025) Table 8 coefficients applied to task-level automation and expertise scores",
      "caveat": "Coefficients were estimated on 1980-2018 computerization. Applying them to AI-era exposure is an out-of-sample transfer.",
      "distributionVintage": "2026-09-29 (928 careers)"
    },
    "laborMarket": {
      "medianWage": 135980,
      "medianWageSource": "oews_national",
      "employment2024": 1656000,
      "employment2034": 1800000,
      "employmentChangePctBLS": 8.7,
      "annualOpeningsBLS": 140100,
      "educationRequired": "Bachelor's degree",
      "experienceRequired": "None",
      "trainingRequired": "None",
      "dataSource": "direct"
    },
    "local": {
      "area": { "code": "14460", "title": "Boston-Cambridge-Newton, MA-NH", "state": "MA", "type": "metro" },
      "workers": 42310,
      "medianWage": 166090,
      "locationQuotient": 1.44,
      "national": { "workers": 1687890, "medianWage": 135980 },
      "vintage": "May 2025 OEWS"
    },
    "hierarchy": {
      "parents": {
        "major": { "code": "15-0000", "name": "Computer and Mathematical Occupations", "slug": "computer-and-mathematical-occupations", "url": "https://www.airesilience.org/career/computer-and-mathematical-occupations" },
        "minor": { "code": "15-1200", "name": "Computer Occupations", "slug": "computer-occupations", "url": "https://www.airesilience.org/career/computer-occupations" },
        "broad": { "code": "15-1250", "name": "Software and Web Developers, Programmers, and Testers", "slug": "software-and-web-developers-programmers-and-testers", "url": "https://www.airesilience.org/career/software-and-web-developers-programmers-and-testers" }
      },
      "siblings": [
        { "code": "15-1253.00", "name": "Software Quality Assurance Analysts and Testers", "slug": "software-quality-assurance-analysts-and-testers", "url": "https://www.airesilience.org/career/software-quality-assurance-analysts-and-testers" }
      ],
      "children": []
    },
    "lastUpdated": "2026-05-16"
  }
}

Bulk (List) Endpoint

Returns a summary list of all occupations. Useful for syncing the dataset or building filtered views client-side. Each entry is a compact summary (resilience score, label, confidence) — for the full per-occupation payload, call the single-career endpoint with the SOC code.

Query Parameters

All parameters are optional. When neither page nor pageSize is supplied, the endpoint returns the full unpaginated list.

Response Fields

Example Response (paginated)

GET /ext/api/careers?level=detailed&page=1&pageSize=2

{
  "success": true,
  "data": [
    {
      "code": "11-1011.00",
      "name": "Chief Executives",
      "slug": "chief-executives",
      "level": "detailed",
      "url": "https://www.airesilience.org/career/chief-executives",
      "aiResilience": {
        "score": 0.78,
        "label": "Resilient",
        "confidence": "High"
      }
    },
    {
      "code": "11-1021.00",
      "name": "General and Operations Managers",
      "slug": "general-and-operations-managers",
      "level": "detailed",
      "url": "https://www.airesilience.org/career/general-and-operations-managers",
      "aiResilience": {
        "score": 0.61,
        "label": "Mostly Resilient",
        "confidence": "Medium-high"
      }
    }
  ],
  "meta": {
    "total": 867,
    "page": 1,
    "pageSize": 2,
    "totalPages": 434,
    "hasMore": true,
    "lastUpdated": "2026-05-16"
  }
}

Search Endpoint

Search occupations by title keyword. Returns the same summary shape as the bulk endpoint, ranked by where the match occurs (earlier in the title = higher rank).

Query Parameters

Example Response

GET /ext/api/careers/search?q=software&limit=2

{
  "success": true,
  "data": [
    {
      "code": "15-1252.00",
      "name": "Software Developers",
      "slug": "software-developers",
      "level": "detailed",
      "url": "https://www.airesilience.org/career/software-developers",
      "aiResilience": { "score": 0.62, "label": "Mostly Resilient", "confidence": "High" }
    },
    {
      "code": "15-1253.00",
      "name": "Software Quality Assurance Analysts and Testers",
      "slug": "software-quality-assurance-analysts-and-testers",
      "level": "detailed",
      "url": "https://www.airesilience.org/career/software-quality-assurance-analysts-and-testers",
      "aiResilience": { "score": 0.58, "label": "Mostly Resilient", "confidence": "Medium-high" }
    }
  ],
  "meta": {
    "query": "software",
    "total": 7,
    "limit": 2,
    "truncated": true,
    "lastUpdated": "2026-05-16"
  }
}

Tasks Endpoint

Tasks-only view of a single occupation. Returns the same tasks array as the single-career endpoint, plus minimal occupation identity. Useful when you only need task-level resilience scores and want a smaller payload.

Example Response

GET /ext/api/career/15-1252.00/tasks

{
  "success": true,
  "data": {
    "code": "15-1252.00",
    "name": "Software Developers",
    "slug": "software-developers",
    "level": "detailed",
    "url": "https://www.airesilience.org/career/software-developers",
    "tasks": [
      {
        "id": "1",
        "task": "Confer with systems analysts, engineers, programmers and others...",
        "taskType": "Core",
        "automationLikelihood": 0.18,
        "resilienceScore": 0.82,
        "expertiseLevel": 0.55,
        "analysisDate": "2026-05-16"
      }
    ]
  }
}

Report Endpoint

The narrative "Career Report" for an occupation — the written analysis shown on the career page. Returns an ordered array of content sections: the AI resilience summary, the deep-research analysis paragraphs, the AI replacement verdict, and suggested actions. Section content is markdown-formatted text.

Response Fields

Alongside the occupation identity (code, name, slug, level, reportUrl), the content lives in data.careerReport, an ordered array of sections.

Example Response

GET /ext/api/career/15-1252.00/report

{
  "success": true,
  "data": {
    "code": "15-1252.00",
    "name": "Software Developers",
    "slug": "software-developers",
    "level": "detailed",
    "reportUrl": "https://www.airesilience.org/career/software-developers",
    "careerReport": [
      {
        "type": "Summary",
        "title": "AI Resilience Summary",
        "content": "Software developers are mostly resilient to AI impacts..."
      },
      {
        "type": "resilienceParagraph",
        "title": "How is AI changing Software Developers jobs?",
        "content": "How is AI changing Software Developers jobs?\n\nRight now, AI in software development is leaning much more toward augmentation than full automation..."
      },
      {
        "type": "replacementVerdict",
        "title": "AI Replacement Verdict",
        "content": "Will AI replace software developers? Not in the near term..."
      },
      {
        "type": "suggestedActions",
        "title": "Suggested Actions",
        "content": "- Build a portfolio of end-to-end projects...\n- Develop fluency with AI-assisted coding tools..."
      }
    ]
  }
}

Local Areas Endpoint

The full per-area table for one occupation: every metro and nonmetro area's workers, median annual wage, and location quotient, plus the national figures. Same BLS OEWS data as the local block on the single-career endpoint, all ~530 areas at once. Detailed occupation codes resolve to their OEWS occupation (combined-occupation alias or SOC broad group where needed); aggregate SOC levels and military occupations return 404 GEO_NOT_AVAILABLE. Suppressed BLS values are null, never zero.

Query Parameters

All parameters are optional.

Example Response

GET /ext/api/career/15-1252.00/local?state=MA&sort=workers

{
  "success": true,
  "data": {
    "code": "15-1252.00",
    "occCode": "15-1252",
    "title": "Software Developers",
    "national": { "workers": 1687890, "medianWage": 135980 },
    "areaCount": 5,
    "areas": [
      {
        "code": "14460",
        "title": "Boston-Cambridge-Newton, MA-NH",
        "state": "MA",
        "type": "metro",
        "workers": 42310,
        "medianWage": 166090,
        "locationQuotient": 1.44
      },
      {
        "code": "49340",
        "title": "Worcester, MA-CT",
        "state": "MA",
        "type": "metro",
        "workers": 4160,
        "medianWage": 139560,
        "locationQuotient": 0.71
      }
    ],
    "vintage": "May 2025 OEWS"
  }
}

Area Search Endpoint

Area discovery: how a consumer goes from a place name like "boston" to the area ID the career endpoints take as ?area=. With no parameters it returns the full directory of ~530 OEWS areas. The list changes once a year with the OEWS release, so responses cache hard.

Query Parameters

All parameters are optional.

Example Response

GET /ext/api/geo/areas?q=boston, ma

{
  "success": true,
  "data": {
    "areas": [
      {
        "code": "14460",
        "title": "Boston-Cambridge-Newton, MA-NH",
        "state": "MA",
        "type": "metro",
        "matchedPlace": "Boston, MA"
      }
    ],
    "count": 1,
    "vintage": "May 2025 OEWS"
  }
}

Error Responses

Rate Limiting

The API is rate limited to 100 requests per minute per IP address using a sliding window. If you hit the limit, you'll receive a 429 response with a Retry-After header indicating how many seconds to wait.

CORS

This API supports cross-origin requests from any domain. You can call it directly from browser-based applications without a proxy.

MCP Server for AI Assistants

We provide a Model Context Protocol (MCP) server that wraps this API, allowing AI assistants like Claude to look up career resilience data directly. No API key required.

Install via npm: ai-resilience-mcp

Configuration

Add the following to your MCP client configuration:

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "ai-resilience": {
      "command": "npx",
      "args": ["-y", "ai-resilience-mcp"]
    }
  }
}

Claude Code

Add to your project's .mcp.json:

{
  "mcpServers": {
    "ai-resilience": {
      "command": "npx",
      "args": ["-y", "ai-resilience-mcp"]
    }
  }
}

Available Tools

Notable changes to the API. Breaking changes are called out explicitly.