Podcast Commerce Mcp

io.github.teamsincetoday由 GitHub 账号 teamsincetoday 发布v0.1.3更新于 Oct 24, 2026

Extract product mentions from podcast transcripts with affiliate signals. Free tier 200/day.

已验证STDIO仅桌面数据与分析商业与电商媒体与设计

概览

AI 生成的概览

从播客文字稿中提取产品与赞助商提及，附带置信度、推荐强度和联盟营销信号。

可以做什么
  • 从文字稿中提取产品与品牌，含说话人、上下文、置信度与推荐强度
  • 识别赞助商片段并估算口播完读率
  • 跨多期节目比较产品提及，判断上升或下降趋势
  • 跨多个节目对产品排名，做实体归并并给出共识程度
  • 把已提取的产品整理成可购物的节目笔记段落
适用场景
适合播客制作方、联盟营销人员或分析人员，让助手从节目文字稿中挖掘产品植入、赞助口播和跨节目品牌趋势，并起草可购物的节目笔记。
运行要求
通过 npm 包 podcast-commerce-mcp 以 stdio 在本地运行（需 Node.js 与 npx）。产品提取需要 OPENAI_API_KEY 中的 OpenAI API 密钥。可选 MCP_API_KEYS 用于付费无限调用，另有 AGENT_ID、CACHE_DIR、PAYMENT_ENABLED 等可选设置。README 另提到一个托管端点。
安装前请注意
必须提供 OPENAI_API_KEY，文字稿内容会发送给 OpenAI 做提取，机密或未发布内容应避免使用。付费按次计费并需配置 MCP_API_KEYS；免费额度为每天 200 次调用。趋势与节目笔记工具只能处理此前已提取并缓存的节目。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Podcast Commerce Mcp，将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only，通过 STDIO。 STDIO 服务会启动本地进程，因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

README

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

bash
# Installnpm install podcast-commerce-mcp
# Configurecp .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:

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

MCP Client Config (local/stdio)

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

Tool Reference

extract_podcast_products

json
{  "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:

json
{  "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

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

track_product_trends

json
{  "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

json
{  "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

json
{  "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):

json
{  "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

bash
npm installnpm run typecheck   # Zero type errorsnpm test            # All tests passnpm run build       # Compile to dist/

License

MIT — Since Today Studio

来源：README.md，提交 d74d42a

工具

0
SourceWeft 尚未在沙箱中启动过该软件包，因此其工具未知。

版本历史

1
  1. v0.1.3最新Sep 16, 2026

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