Podcast Commerce Intelligence

Extract product mentions, sponsors, and trends from podcast transcripts.

CommunityOnlineNo sign-inGlobalFreeRead-only

What it can do

  • Extract Podcast Products: Extract product and brand mentions from a podcast transcript. Returns structured data including product name, category, confidence score, recommendation strength, and sponsor
  • Analyze Episode Sponsors: 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 met
  • Track Product Trends: Compare product mentions across multiple podcast episodes to identify rising, stable, and falling product trends. Requires episodes to have been previously extracted (via extract

What data it sees

Do you need an account

No: the server works without sign-in

Extract product mentions, sponsors, and trends from podcast transcripts. Returns structured data with product names, categories, confidence scores, recommendation strength, and aesthetic tags. Tools: extract_podcast_products, analyze_episode_sponsors, track_product_trends (with avg_recommendation_strength), compare_products_across_shows, generate_show_notes_section. Free tier: 200 calls/day. $0.01/call paid.

How to connect

How to connect Podcast Commerce Intelligence to Claude

The server address to paste into Claude settings:

https://podcast-commerce-mcp--sincetoday.run.tools

  1. Open Claude (claude.ai or the desktop app).
  2. Go to Settings → Connectors.
  3. Click Add custom connector.
  4. Paste the server address copied below into Remote MCP server URL and click Add.
  5. In a chat, click + → Connectors and switch the new connector on.

Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

Authorization

After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

How to connect Podcast Commerce Intelligence to ChatGPT

The server address to paste into ChatGPT settings:

https://podcast-commerce-mcp--sincetoday.run.tools

  1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
  2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
  3. Open Settings → Connectors and click Create.
  4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
  5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
  6. In a new chat open + → Apps/Connectors and enable the connector.

OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

Authorization

On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

How to connect Podcast Commerce Intelligence to Cursor

The server address to paste into Cursor settings:

https://podcast-commerce-mcp--sincetoday.run.tools

Fastest: click Open in Cursor below and confirm the prompt.

Manually:

  1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
  2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
  3. Save the file. The server appears in the MCP list; authorize it there if asked.

Authorization

If the service needs sign-in, an authorize button appears next to the server in the MCP list.

Server tool list (5)

Raw names from tools/list. Only developers need these.

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.
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.
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.
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 per-show context, average confidence, and recommendation consensus. Use for multi-show affiliate research, best-of page generation, and cross-show brand ranking. Supports physical_goods, saas, supplement, and all other categories. Requires prior extract_podcast_products calls for each show_id.
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 episode_id to use cached extraction, or pass products[] directly. Handles null affiliate_link gracefully (shows product name without link). Format: markdown (default) produces copy-paste text for show notes editors; html produces embeddable markup. Style: full (default) groups by endorsement with context quotes; minimal produces a compact list.