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Podcast Commerce Mcp

teamsincetoday/podcast-commerce-mcp
5 toolsauthSTDIO, HTTPregistry active
Summary

Connects Claude to podcast transcript analysis with five extraction tools: pull product mentions with confidence scores and recommendation strength, identify sponsor segments with read-through estimates, track product trends across episodes, compare mentions across multiple shows, and generate formatted shoppable show notes. Returns structured JSON with speaker attribution, affiliate network signals, and category labels. Runs on OpenAI embeddings with SQLite caching. Free tier gives you 200 calls per day through their hosted endpoint, or run it locally via stdio. Built for podcasters and affiliate marketers who need to turn long-form audio transcripts into monetizable product databases without manual tagging.

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Tools

Public tool metadata for what this MCP can expose to an agent.

5 tools
extract_podcast_productsExtract product and brand mentions from a podcast transcript. Returns structured data including product name, category, confidence score, recommendation strength, and sponsor segments. Supports caching by episode_id.4 params

Extract product and brand mentions from a podcast transcript. Returns structured data including product name, category, confidence score, recommendation strength, and sponsor segments. Supports caching by episode_id.

Parameters* required
api_keystring
Optional API key for paid access beyond the free tier
episode_idstring
Optional episode identifier for caching and trend tracking
transcriptstring
Raw transcript text OR a URL to a .txt transcript file
category_filterarray
Optional list of categories to include: physical_goods, saas, course, book, service, affiliate, other
analyze_episode_sponsorsIdentify sponsor segments in a podcast episode and estimate read-through rates. Returns sponsor list, read type (host-read, mid-roll, etc.), call-to-action, and aggregate metrics. Uses cached extraction if episode_id was previously processed.3 params

Identify sponsor segments in a podcast episode and estimate read-through rates. Returns sponsor list, read type (host-read, mid-roll, etc.), call-to-action, and aggregate metrics. Uses cached extraction if episode_id was previously processed.

Parameters* required
api_keystring
Optional API key for paid access beyond the free tier
episode_idstring
Optional episode identifier — uses cached extraction if available
transcriptstring
Raw transcript text OR a URL to a .txt transcript file
track_product_trendsCompare product mentions across multiple podcast episodes to identify rising, stable, and falling product trends. Requires episodes to have been previously extracted (via extract_podcast_products) and cached by episode_id.3 params

Compare product mentions across multiple podcast episodes to identify rising, stable, and falling product trends. Requires episodes to have been previously extracted (via extract_podcast_products) and cached by episode_id.

Parameters* required
api_keystring
Optional API key for paid access beyond the free tier
episode_idsarray
List of episode IDs to analyze. Each must have been previously extracted via extract_podcast_products.
category_filterarray
Optional category filter to narrow trend analysis
compare_products_across_showsCompare and rank product mentions across multiple podcast shows using cached extractions — no re-run. Collapses a 3-call manual join into 1 tool call. Performs entity resolution to identify the same product mentioned across shows. Returns ranked cross-show product list with pe...5 params

Compare and rank product mentions across multiple podcast shows using cached extractions — no re-run. Collapses a 3-call manual join into 1 tool call. Performs entity resolution to identify the same product mentioned across shows. Returns ranked cross-show product list with pe...

Parameters* required
api_keystring
Optional API key for paid access beyond the free tier
categorystring
Optional single-category filter: physical_goods, saas, course, service, supplement, media, event, other
show_idsarray
List of show/episode IDs to compare. Each must have a prior extract_podcast_products cache entry.
min_confidencenumber
Minimum confidence threshold (default 0.85). Lower to include more products.
min_show_countinteger
Minimum number of shows a product must appear in (default 2). Set to 1 for single-show results.
generate_show_notes_sectionFormat extracted podcast products into a shoppable show notes section. Returns a ready-to-paste markdown or HTML product list, grouped by endorsement strength (strong/moderate/mention), with affiliate links where resolved. Use after extract_podcast_products — either pass episo...5 params

Format extracted podcast products into a shoppable show notes section. Returns a ready-to-paste markdown or HTML product list, grouped by endorsement strength (strong/moderate/mention), with affiliate links where resolved. Use after extract_podcast_products — either pass episo...

Parameters* required
stylestring
minimal = name + category list; full (default) = grouped by endorsement strength with context quotesone of minimal · full
formatstring
Output format: markdown (default) or htmlone of markdown · html
api_keystring
Optional API key for paid access beyond the free tier
productsarray
Raw products array from extract_podcast_products output. Use instead of episode_id when passing data directly.
episode_idstring
Episode identifier from a prior extract_podcast_products call — uses cached extraction. Example: 'huberman-lab-ep-123'

Podcast Commerce Intelligence MCP

npm License: MIT Stars

Turn podcast transcripts into affiliate revenue. Give any episode transcript to an AI agent — get back every product mentioned, who said it, how strongly they recommended it, and which affiliate network carries it. F1=100% on eval suite. Free tier: 200 calls/day.

⭐ If this saves you time, please star the repo — it helps other developers find it.

Live endpoint: https://podcast-commerce-mcp.sincetoday.workers.dev/mcp · See examples

Extract product mentions, sponsor segments, and product trends from podcast transcripts. Built on x402, the open payment standard backed by Shopify, Google, Microsoft, Visa, and the Linux Foundation.

Tools

ToolDescription
extract_podcast_productsExtract products/brands from a transcript with confidence scores
analyze_episode_sponsorsIdentify sponsor segments and estimate read-through rates
track_product_trendsCompare product mentions across multiple episodes
compare_products_across_showsCross-show product ranking with entity resolution across multiple shows
generate_show_notes_sectionFormat extracted products as a shoppable show notes section

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

Connect in Claude Code — No Install Required

Add to your claude_desktop_config.json or use /add-mcp in Claude Code. Free tier: 200 calls/day, no API key needed:

{
  "mcpServers": {
    "podcast-commerce": {
      "url": "https://podcast-commerce-mcp.sincetoday.workers.dev/mcp"
    }
  }
}

MCP Client Config (local/stdio)

{
  "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. Returns trends[] with brand, trend (rising/stable/falling), avg_recommendation_strength, and top_category.

compare_products_across_shows

{
  "show_ids": ["show-a", "show-b"],
  "min_show_count": 2,
  "min_confidence": 0.85
}

Ranks products by how many shows mention them. Returns products[] with brand, show_count, avg_confidence, recommendation_consensus (unanimous/majority/mixed/rare).

generate_show_notes_section

{
  "episode_id": "previously-extracted-id",
  "format": "markdown",
  "style": "full"
}

Formats cached product data as a shoppable show notes block. Returns a formatted string ready to paste into episode notes.

Example Output

Real extraction from a Huberman Lab episode transcript (live eval: F1=89%, 96/100 score, $0.00046/call, 8100ms):

{
  "episode_id": "huberman-ep-312",
  "products": [
    {
      "name": "AG1 (Athletic Greens)",
      "brand": "AG1",
      "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

VariableRequiredDefaultDescription
OPENAI_API_KEYYes—OpenAI API key
AGENT_IDNoanonymousAgent identifier for rate limiting
MCP_API_KEYSNo—Comma-separated paid API keys
CACHE_DIRNo./data/cache.dbSQLite cache path
PAYMENT_ENABLEDNofalseSet 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

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Configuration

OPENAI_API_KEY*secret

OpenAI API key for GPT-4o-mini product extraction (required)

MCP_API_KEYSsecret

Comma-separated paid API keys for unlimited calls (optional — omit for free tier: 200 calls/day)

Categories
Search & Web CrawlingFinance & CommerceMedia & Entertainment
Registryactive
Packagepodcast-commerce-mcp
TransportSTDIO, HTTP
AuthRequired
UpdatedApr 4, 2026
View on GitHub

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