{
  "name": "Orbyt Intelligence",
  "description": "Orbyt Intelligence MCP server for AI and tech compensation. Six Decision-Ready tools covering personalized salary estimates, skill premiums, market signals, role and city discovery, and adjacent-role transitions across 3,445 AI and tech roles and 81 U.S. cities. Every tool returns a Decision-Ready Response with an agent-quotable answer, the methodology version, and a citation carrying a request_id. The MCP server requires the Pro plan or higher; the hosted endpoint rejects free-tier keys with a 403. There is no trial; a paid subscription bills immediately. There is a free tier: 60 requests/minute and 1,000 requests/month on the REST API, API key required, no card. Paid plans start at Pro ($99/mo). Generate an API key at https://www.orbytjobs.ai/intelligence/dashboard.",
  "url": "https://www.orbytjobs.ai/orbyt-intelligence/mcp",
  "mcp_endpoint": "https://www.orbytjobs.ai/api/v1/intelligence/mcp",
  "protocol_versions": ["2025-11-25", "2025-06-18", "2025-03-26", "2024-11-05"],
  "transport": "JSON-RPC 2.0 over HTTP POST. Discover tools with the tools/list method and invoke them with tools/call. The server negotiates official MCP protocol versions during initialize (echoes a supported requested version, otherwise answers with 2025-11-25), so official-SDK clients such as Claude Desktop and Claude Code connect through the mcp-remote bridge; the working config is at https://www.orbytjobs.ai/downloads/orbyt-claude-desktop.json. The MCP server requires the Pro plan or higher. Free-tier keys receive a 403 with an upgrade link.",
  "auth": {
    "type": "bearer",
    "instructions": "Bearer token required on every tier, including free, because the monthly limit is metered per user. The MCP server is available on Pro and above, and there is no trial: a paid subscription bills immediately. Subscribe at https://www.orbytjobs.ai/intelligence/signup and generate an API key at https://www.orbytjobs.ai/intelligence/dashboard. Free ($0): 60 req/min, 1,000 requests/month, REST API, no card. Pro ($99/mo or $990/yr): 300 req/min, 250,000 requests/month, plus the MCP server and the /lineage endpoint. Ultra ($199/mo or $1,999/yr): 1,500 req/min, 500,000 requests/month, plus the company leveling catalog and the annual compensation reports."
  },
  "documentation": {
    "mcp": "https://www.orbytjobs.ai/orbyt-intelligence/mcp",
    "openapi": "https://www.orbytjobs.ai/openapi-intelligence.yaml",
    "website": "https://www.orbytjobs.ai/intelligence",
    "methodology": "https://www.orbytjobs.ai/orbyt-intelligence/methodology"
  },
  "tools": [
    {
      "name": "list_capabilities",
      "description": "Returns the catalog of available Orbyt Intelligence MCP tools. Call this first to discover what is possible.",
      "tier_required": "pro",
      "scopes_required": [],
      "output_shape": "decision-ready-response",
      "parameters": {}
    },
    {
      "name": "analyze_compensation",
      "description": "Personalized salary estimate for a role plus city plus experience level. Returns a total compensation breakdown, percentile bands, and methodology-grade transparency. Supports analysis_type of estimate, history, projection, or offer_assessment.",
      "tier_required": "pro",
      "scopes_required": ["intelligence:read"],
      "output_shape": "decision-ready-response",
      "parameters": {
        "role": { "type": "string", "description": "Role slug (e.g., 'ai-engineer'). Use discover_roles_and_cities to find canonical slugs.", "required": true },
        "city": { "type": "string", "description": "City slug (e.g., 'san-francisco').", "required": true },
        "experience": { "type": "string", "description": "entry | mid | senior | staff. Default 'mid'.", "required": false },
        "analysis_type": { "type": "string", "description": "estimate | history | projection | offer_assessment. Default 'estimate'.", "required": false },
        "offer": { "type": "object", "description": "Used when analysis_type='offer_assessment'. {base_salary}.", "required": false },
        "through": { "type": "number", "description": "Used when analysis_type='projection'. Forecast through this year (default 2027).", "required": false },
        "as_of": { "type": "string", "description": "Used when analysis_type='history'. Time-travel to this date (YYYY-MM-DD).", "required": false },
        "country": { "type": "string", "description": "ISO 3166-1 alpha-2 (US | GB | CA). Default 'US'. GB and CA accept the parameter; Tier 1 international data is rolling out and the response discloses the limitation explicitly.", "required": false }
      }
    },
    {
      "name": "analyze_skills",
      "description": "Skill premiums and half-life for a role. Returns which skills boost compensation, by how much, and which are decaying.",
      "tier_required": "pro",
      "scopes_required": ["intelligence:read", "skills:read"],
      "output_shape": "decision-ready-response",
      "parameters": {
        "role": { "type": "string", "description": "Role slug.", "required": true },
        "city": { "type": "string", "description": "Optional. National aggregate when omitted.", "required": false },
        "include_half_life": { "type": "boolean", "description": "When true, includes skill trajectory analysis.", "required": false },
        "country": { "type": "string", "description": "ISO 3166-1 alpha-2 (US | GB | CA). Default 'US'.", "required": false }
      }
    },
    {
      "name": "analyze_market",
      "description": "Hiring velocity and market signals for a role: time-to-fill, trend (lengthening | stable | shortening), and market baseline.",
      "tier_required": "pro",
      "scopes_required": ["intelligence:read", "market:read"],
      "output_shape": "decision-ready-response",
      "parameters": {
        "role": { "type": "string", "description": "Role slug.", "required": true },
        "city": { "type": "string", "description": "City slug.", "required": true },
        "country": { "type": "string", "description": "ISO 3166-1 alpha-2 (US | GB | CA). Default 'US'.", "required": false }
      }
    },
    {
      "name": "discover_roles_and_cities",
      "description": "Browse the role and city catalog or full-text search across roles. Use this to find canonical slugs before calling the analyze tools.",
      "tier_required": "pro",
      "scopes_required": ["intelligence:read"],
      "output_shape": "decision-ready-response",
      "parameters": {
        "query": { "type": "string", "description": "Optional full-text search. When omitted, returns the catalog.", "required": false },
        "kind": { "type": "string", "description": "roles | cities | both. Default 'both'.", "required": false },
        "limit": { "type": "number", "description": "1 to 100.", "required": false },
        "country": { "type": "string", "description": "ISO 3166-1 alpha-2 (US | GB | CA). Default 'US'. Scopes the catalog to the jurisdiction.", "required": false }
      }
    },
    {
      "name": "find_adjacent_opportunities",
      "description": "Career-adjacent roles for the given role, ranked by transition feasibility and compensation delta.",
      "tier_required": "pro",
      "scopes_required": ["intelligence:read"],
      "output_shape": "decision-ready-response",
      "parameters": {
        "role": { "type": "string", "description": "Role slug.", "required": true },
        "count": { "type": "number", "description": "Number of adjacent roles to return (1 to 20). Default 5.", "required": false },
        "country": { "type": "string", "description": "ISO 3166-1 alpha-2 (US | GB | CA). Default 'US'.", "required": false }
      }
    }
  ],
  "examples": {
    "discover_first": {
      "description": "Call list_capabilities, then discover canonical role and city slugs before analysis.",
      "tool": "discover_roles_and_cities",
      "arguments": { "query": "machine learning", "kind": "both" }
    },
    "personalized_estimate": {
      "description": "Get a personalized estimate with an agent-quotable answer and a citation.",
      "tool": "analyze_compensation",
      "arguments": { "role": "ai-engineer", "city": "san-francisco", "experience": "senior" }
    },
    "offer_assessment": {
      "description": "Compare an offer against the market.",
      "tool": "analyze_compensation",
      "arguments": { "role": "ml-engineer", "city": "new-york", "analysis_type": "offer_assessment", "offer": { "base_salary": 210000 } }
    }
  },
  "pricing": {
    "free": {
      "price": "$0",
      "rate_limit": "60 requests/minute",
      "monthly_quota": "1,000 requests/month",
      "features": ["AI Role Taxonomy engine", "Published BLS wage benchmarks", "Calculate endpoint", "Search endpoint", "3,445 roles", "81 cities", "54 company frameworks", "Compare offers", "REST API", "API key required, no card"]
    },
    "pro": {
      "price": "$99/month or $990/year",
      "rate_limit": "300 requests/minute",
      "monthly_quota": "250,000 requests/month",
      "features": ["Everything in Free", "Full quarterly history", "MCP server (6 tools)", "Lineage endpoint", "Restricted API keys with per-engine scopes", "Priority support"]
    },
    "ultra": {
      "price": "$199/month or $1,999/year",
      "rate_limit": "1,500 requests/minute",
      "monthly_quota": "500,000 requests/month",
      "features": ["Everything in Pro", "Company leveling catalog", "Annual compensation reports", "Dedicated support", "Custom data requests"]
    }
  }
}