Track Podcasts
Podcast sponsorship data from transcribed audio: who sponsors which shows, brand ad history, trends.
Should I use this
Quality & Safety
Based on automated analysis of tool definitions and protocol compliance.
Context Cost
This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.
Install
One-Click Install
Add this to your `claude_desktop_config.json` file:
{
"mcpServers": {
"podcast-sponsors": {
"url": "https://trackpodcasts.com/api/mcp"
}
}
}Remote endpoints
https://trackpodcasts.com/api/mcpstreamable-httpWhat it can do
Tool inventory
Tools (5)
🟢get_show_sponsors(show)
Who sponsors a given podcast. Returns every brand whose ad read was detected in that show's transcribed episodes, with how many reads, whether they were host-read or network-inserted, and when they were first and last heard. Accepts a show title, a trackpodcasts.com slug or a URL. If the title is ambiguous it returns candidate shows to choose from instead of guessing. Detected ad reads only — brands that were merely mentioned are not included.
Input Schema
{
"type": "object",
"properties": {
"show": {
"type": "string",
"description": "Podcast title, slug or trackpodcasts.com URL, e.g. \"The Glenn Beck Program\"."
}
},
"required": [
"show"
],
"additionalProperties": false
}🟢get_brand_podcasts(brand)
Which podcasts a brand advertises on. Returns the shows where that brand's ad reads were detected, newest first, with the exact total even when the list itself is truncated for the plan. Accepts a brand name, slug or domain (a domain is the most reliable). Returns candidate brands when the name is ambiguous.
Input Schema
{
"type": "object",
"properties": {
"brand": {
"type": "string",
"description": "Brand name, slug or domain, e.g. \"Squarespace\" or \"squarespace.com\"."
}
},
"required": [
"brand"
],
"additionalProperties": false
}🟢get_sponsor_activity_summary(brand, months)
How a brand’s podcast advertising has moved month by month: shows reached, ad reads detected and organic mentions, for up to 36 months. Use this for trend questions ("is this brand spending more?", "when did they start?"). Months with no detections are returned as zero, which means nothing was detected rather than that the brand stopped.
Input Schema
{
"type": "object",
"properties": {
"brand": {
"type": "string",
"description": "Brand name, slug or domain."
},
"months": {
"type": "integer",
"minimum": 1,
"maximum": 36,
"description": "Months of history to return. Defaults to 12."
}
},
"required": [
"brand"
],
"additionalProperties": false
}🟢get_coverage_info
How much of podcasting this dataset actually covers: shows indexed, episodes transcribed, and the real number of brands and shows with detected ad reads. Call this before stating any sponsor finding as complete, and to explain why a show or brand might be missing.
Input Schema
{
"type": "object",
"properties": {},
"additionalProperties": false
}🟢get_busiest_categories(days)
Which advertiser categories are buying the most podcast ads right now, by ad reads detected, with the number of brands and shows behind each. Aggregate only — it does not list the brands in a category.
Input Schema
{
"type": "object",
"properties": {
"days": {
"type": "integer",
"enum": [
30,
90,
365
],
"description": "Lookback window in days. Defaults to 30."
}
},
"additionalProperties": false
}Community
Evidence