Newsletter Commerce Mcp

io.github.teamsincetoday由 GitHub 帳號 teamsincetoday 發布v0.1.3更新於 Oct 24, 2026

Extract shoppable products from newsletter content with affiliate signals.

已驗證STDIO僅桌面效率與工作流商業與電商

概覽

AI 產生的概覽

一個本機 MCP 伺服器,從電子報中擷取可購買產品、贊助商與聯盟行銷訊號,並產生可直接貼上的產品清單。

可以做什麼
從 HTML 或純文字電子報中擷取產品、聯盟連結和贊助商提及,提供每個產品的信心度與推薦強度,並依 newsletter ID 快取結果。依預估 CPM、閱讀率和受眾契合度為贊助商區塊評分。比對多個已擷取期號中的產品提及,找出熱門產品、類別和品牌趨勢。將擷取結果格式化為 markdown 或 HTML 的「本期產品」區塊,支援完整或精簡樣式。
適用情境
適合電子報作者、聯盟行銷人員和編輯,用來從 Substack、Ghost、Beehiiv 或純文字期號中挖掘產品與贊助商提及、跨期比較趨勢,並草擬可購買的產品頁尾,而不必逐篇人工閱讀。
執行需求
透過 npm 套件 newsletter-commerce-mcp 以 stdio 在本機執行,需要 Node.js 和 npx。產品擷取需要 OPENAI_API_KEY 中的 OpenAI API 金鑰。選用設定包括付費呼叫用的 MCP_API_KEYS、用於限流的 AGENT_ID、SQLite 快取路徑 CACHE_DIR 以及 PAYMENT_ENABLED。呼叫 OpenAI 需要網路存取。
安裝前請注意
電子報內容會傳送給 OpenAI 進行擷取,請勿貼上機密或訂閱者資料。OpenAI 金鑰是可計費憑證,每次擷取都會產生 AI 費用。設定 MCP_API_KEYS 後每次呼叫計費 0.01 美元,PAYMENT_ENABLED 可強制執行額度。擷取的聯盟連結和贊助商評分僅為估算,並非查證過的資料。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Newsletter Commerce Mcp,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

Newsletter Commerce Intelligence MCP

[npm] [License: MIT] [Stars]

Turn newsletters into affiliate revenue. Extract sponsored products, brand mentions, and affiliate signals from any Substack, Ghost, or Beehiiv issue. Then auto-generate a shoppable "Products in this edition" section ready to paste into your newsletter. 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://newsletter-commerce-mcp.sincetoday.workers.dev/mcp · See examples

Extract product mentions, score sponsors, and track affiliate trends from newsletters. Supports Substack, Ghost, Beehiiv, and plain text. Built on x402, the open payment standard backed by Shopify, Google, Microsoft, Visa, and the Linux Foundation.

Tools

ToolDescription
extract_newsletter_productsExtract products, affiliate links, and sponsor mentions from a newsletter issue
analyze_newsletter_sponsorsScore sponsor sections by CPM, read-through rate, and audience fit
track_product_trendsCompare product mentions across multiple newsletter issues to surface trending products and brand patterns
generate_newsletter_products_sectionFormat extracted products into a 'Products in This Edition' footer section (markdown or HTML)

Quick Start

bash
# Installnpm install newsletter-commerce-mcp
# Configurecp .env.example .env# Edit .env: set OPENAI_API_KEY
# Run (stdio MCP server)npx newsletter-commerce-mcp

MCP Client Config

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

Tool Reference

extract_newsletter_products

json
{  "content": "Newsletter HTML or plain text (max 200k chars)",  "newsletter_id": "optional-cache-key",  "format": "html",  "api_key": "optional-paid-key"}

Returns:

json
{  "newsletter_id": "swipe-file-issue-47",  "products": [    {      "name": "Notion AI",      "category": "saas",      "mention_context": "running my entire writing workflow through Notion AI",      "recommendation_strength": "strong",      "affiliate_link": null,      "confidence": 0.94,      "is_sponsored": false    }  ],  "sponsor_sections": [...],  "_meta": { "processing_time_ms": 1620, "ai_cost_usd": 0.0028, "cache_hit": false }}

analyze_newsletter_sponsors

json
{  "content": "Newsletter HTML or plain text",  "newsletter_id": "optional",  "api_key": "optional"}

Returns CPM estimate, read-through rate, and sponsor-reader fit score per sponsor section.

track_product_trends

json
{  "newsletter_ids": ["issue-45", "issue-46", "issue-47"],  "category_filter": ["saas", "books"]}

Requires prior extract_newsletter_products calls for each newsletter_id. Returns trend data including top_category, avg_recommendation_strength, and brand per product trend.

generate_newsletter_products_section

json
{  "newsletter_id": "swipe-file-issue-47",  "format": "markdown",  "style": "full",  "api_key": "optional"}

Formats extracted products into a ready-to-paste 'Products in This Edition' section. Pass newsletter_id (uses cached extraction) or products[] directly. format: markdown (default) or html. style: full (default, grouped by endorsement strength with context quotes) or minimal (compact list).

Example Output

Real extraction from a TLDR Tech newsletter (live eval: F1=88%, 95/100 score, $0.00051/call, 7390ms):

json
{  "newsletter_id": "tldr-2024-03-07",  "products": [    {      "name": "Groq",      "category": "saas",      "mention_context": "Groq has launched public API access — runs Llama 2 at 300 tokens/second",      "confidence": 0.94,      "recommendation_strength": "neutral"    },    {      "name": "Devin (Cognition AI)",      "category": "saas",      "mention_context": "first AI software engineer — benchmarks show it can complete real GitHub issues end-to-end",      "confidence": 0.91,      "recommendation_strength": "strong"    }  ]}

See /examples endpoint for full output with value narrative: https://newsletter-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

來源:README.md,提交 7f1e76a

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

1
  1. v0.1.3最新Sep 16, 2026

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