Podcast Commerce Intelligence MCP

Extract product mentions, sponsor segments, and product trends from podcast transcripts. Built for the agent-to-agent economy.

Tools

| Tool | Description | |------|-------------| | extract_podcast_products | Extract products/brands from a transcript with confidence scores | | analyze_episode_sponsors | Identify sponsor segments and estimate read-through rates | | track_product_trends | Compare product mentions across multiple episodes |

Quick Start

# Install
npm install podcast-commerce-mcp

# Configure
cp .env.example .env
# Edit .env: set OPENAI_API_KEY

# Run (stdio MCP server)
npx podcast-commerce-mcp

MCP Client Config

{
  "mcpServers": {
    "podcast-commerce": {
      "command": "npx",
      "args": ["podcast-commerce-mcp"],
      "env": {
        "OPENAI_API_KEY": "sk-..."
      }
    }
  }
}

Tool Reference

extract_podcast_products

{
  "transcript": "Raw text or URL to a .txt file",
  "episode_id": "optional-cache-key",
  "category_filter": ["saas", "physical_goods"],
  "api_key": "optional-paid-key"
}

Returns:

{
  "episode_id": "...",
  "products": [
    {
      "name": "Notion",
      "category": "saas",
      "mention_context": "I use Notion every day...",
      "speaker": "Host",
      "confidence": 0.9,
      "recommendation_strength": "strong",
      "affiliate_link": null,
      "mention_count": 2
    }
  ],
  "sponsor_segments": [...],
  "_meta": { "processing_time_ms": 1200, "ai_cost_usd": 0.001, "cache_hit": false }
}

analyze_episode_sponsors

{
  "transcript": "...",
  "episode_id": "optional",
  "api_key": "optional"
}

track_product_trends

{
  "episode_ids": ["ep1", "ep2", "ep3"],
  "category_filter": ["saas"]
}

Requires episodes to be previously extracted and cached.

Example Output

Real extraction from a Huberman Lab episode transcript (eval score: F1=0.95, $0.000365/call, 8220ms):

{
  "episode_id": "huberman-ep-312",
  "products": [
    {
      "name": "AG1 (Athletic Greens)",
      "category": "supplement",
      "mention_context": "today's episode is brought to you by AG1. I've been taking it every morning for six months",
      "confidence": 0.97,
      "recommendation_strength": "strong"
    },
    {
      "name": "Oura Ring",
      "category": "physical_goods",
      "mention_context": "I've been wearing it for sleep tracking for two years. They're not a sponsor, just a genuine rec",
      "confidence": 0.95,
      "recommendation_strength": "strong"
    }
  ],
  "sponsor_segments": [
    {
      "sponsor_name": "AG1",
      "read_type": "host_read",
      "estimated_read_through": 0.72,
      "call_to_action": "code HUBERMAN for a free year's supply of Vitamin D"
    }
  ]
}

See /examples endpoint for full output with value narrative: https://podcast-commerce-mcp.sincetoday.workers.dev/examples

Pricing

• Free tier: 200 calls/day per agent (no API key required)
• Paid: $0.01/call — set MCP_API_KEYS with valid keys

Environment Variables

| Variable | Required | Default | Description | |----------|----------|---------|-------------| | OPENAI_API_KEY | Yes | — | OpenAI API key | | AGENT_ID | No | anonymous | Agent identifier for rate limiting | | MCP_API_KEYS | No | — | Comma-separated paid API keys | | CACHE_DIR | No | ./data/cache.db | SQLite cache path | | PAYMENT_ENABLED | No | false | Set true to enforce limits |

Development

npm install
npm run typecheck   # Zero type errors
npm test            # All tests pass
npm run build       # Compile to dist/

License

MIT — Since Today Studio