About io.github.teamsincetoday/podcast-commerce-mcp
io.github.teamsincetoday/podcast-commerce-mcp is an MCP server in the Communication category: extract product mentions from podcast transcripts with affiliate signals. Free tier 200/day.
Install
claude mcp add io-github-teamsincetoday-podcast-commerce-mcp -- npx -y podcast-commerce-mcpnpx -y podcast-commerce-mcpThis server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
Tools (5)
analyze_episode_sponsorsIdentify sponsor segments and estimate read-through rates
Parameters not published.
compare_products_across_showsCross-show product ranking with entity resolution across multiple shows
Parameters not published.
extract_podcast_productsExtract products/brands from a transcript with confidence scores
Parameters not published.
generate_show_notes_sectionFormat extracted products as a shoppable show notes section
Parameters not published.
track_product_trendsCompare product mentions across multiple episodes
Parameters not published.
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README
Podcast Commerce Intelligence MCP
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
| 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 |
compare_products_across_shows |
Cross-show product ranking with entity resolution across multiple shows |
generate_show_notes_section |
Format 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_KEYSwith 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
README copy captured when this server was indexed; it may lag the repository. The original is authoritative.