Fodda Research Agent

{
  "protocolVersion": "0.3.0",
  "name": "Fodda Research Agent",
  "description": "Expert-curated trend, brand, research, and earnings intelligence from named experts' knowledge graphs (220+ graphs across retail, beauty, sports, finance, and institutional data). Delegate a task in natural language — Fodda selects the right tools and returns a synthesized result.",
  "author": "PSFK / Fodda",
  "wellKnownURI": "https://www.fodda.ai/.well-known/agent-card.json",
  "url": "https://mcp.fodda.ai/a2a",
  "version": "1.46.66",
  "provider": {
    "organization": "Fodda (PSFK)",
    "url": "https://www.fodda.ai/"
  },
  "documentationUrl": "https://www.fodda.ai/llms.txt",
  "iconUrl": "https://ucarecdn.com/6e7893d7-6b14-426b-83bc-574a3f72d6bc/foddafavicon.png",
  "supportsAuthenticatedExtendedCard": null,
  "security": [],
  "securitySchemes": {},
  "capabilities": {
    "streaming": false,
    "pushNotifications": false,
    "stateTransitionHistory": false,
    "extensions": null
  },
  "defaultInputModes": [
    "text/plain"
  ],
  "defaultOutputModes": [
    "text/plain",
    "application/json"
  ],
  "skills": [
    {
      "id": "brand-intelligence",
      "name": "Brand Intelligence",
      "description": "Track a brand's trend footprint, competitive context, and market signals across expert-curated graphs.",
      "tags": [
        "brand",
        "competitive",
        "intelligence"
      ],
      "examples": [
        "What is Nike doing?",
        "Brand intelligence for Patagonia"
      ],
      "inputModes": [],
      "outputModes": []
    },
    {
      "id": "trend-search",
      "name": "Trend Search",
      "description": "Search expert-curated knowledge graphs for trends with supporting evidence and source attribution.",
      "tags": [
        "trends",
        "search",
        "research"
      ],
      "examples": [
        "sustainable packaging trends",
        "Gen Z beauty habits"
      ],
      "inputModes": [],
      "outputModes": []
    },
    {
      "id": "deep-research",
      "name": "Deep Research",
      "description": "Full multi-source autonomous research: expert-curated knowledge graphs, earnings-call intelligence, and institutional data, synthesized into a cited editorial report. Returned as an async task — poll tasks/get for the result. API key required; SPT support coming.",
      "tags": [
        "research",
        "report",
        "analysis"
      ],
      "examples": [
        "comprehensive report on Gen Z luxury",
        "detailed analysis of the resale market"
      ],
      "inputModes": [],
      "outputModes": []
    },
    {
      "id": "earnings-intelligence",
      "name": "Cross-Company Earnings Themes",
      "description": "Surface cross-company and industry-level themes from earnings calls — analyst concerns, management commentary, guidance trends, and divergence detection across sectors.",
      "tags": [
        "earnings",
        "financial",
        "intelligence",
        "cross-company"
      ],
      "examples": [
        "what are hotel companies saying about labor costs",
        "where are executives deflecting on margins"
      ],
      "inputModes": [],
      "outputModes": []
    },
    {
      "id": "per-ticker-earnings",
      "name": "Per-Ticker Earnings Intelligence",
      "description": "The strategic truth layer per company: what analysts pressed on, where management deflected, marketing/retail/tech/sustainability activity, CEO intelligence, and market-validated consumer trends — quarterly records with multi-quarter history for 500+ consumer-sector companies.",
      "tags": [
        "earnings",
        "analyst-pressure",
        "activity",
        "validated-trends"
      ],
      "examples": [
        "What are analysts pressing Nike on?",
        "Compare how Lululemon and On Running talk about growth",
        "Show me Costco's analyst Q&A themes",
        "Which consumer trends do KR's earnings validate?"
      ],
      "inputModes": [],
      "outputModes": []
    },
    {
      "id": "expert-consult",
      "name": "Expert Consult",
      "description": "Consult a named Human Agent — a real expert's digital twin that answers in their voice and researches across expert graphs, earnings calls, and market data on your behalf.",
      "tags": [
        "expert",
        "consult",
        "analyst"
      ],
      "examples": [
        "Consult Ben Dietz about culture-led brand strategy",
        "Ask Anu Lingala about 2026 macro trends"
      ],
      "inputModes": [],
      "outputModes": []
    },
    {
      "id": "commissioned-deliverable",
      "name": "Commissioned Deliverable",
      "description": "Commission a finished document from an analyst — a marketing plan, deck review, or trend briefing. The analyst researches, then produces the document in the background; returned as an async job (poll for the artifact). Priced per offering; see each analyst's offerings.",
      "tags": [
        "deliverable",
        "document",
        "analyst",
        "async"
      ],
      "examples": [
        "Commission a marketing plan from Ben Dietz for a Gen-Z skincare launch",
        "Ask for a trend briefing deliverable on resale"
      ],
      "inputModes": [],
      "outputModes": []
    }
  ],
  "conformance": true,
  "conformance_errors": null,
  "homepage": null,
  "repository": null,
  "license": null,
  "pricing": null,
  "contact": null,
  "id": "ad32dd1e-7be4-4029-a158-b6bd18c0927b"
}