# Podcast Guest Intelligence API (`soft_but_savage/podcast-guest-intelligence`) Actor Track podcast guest appearances without manually scanning podcast apps. It converts podcast RSS feeds into structured records with episode metadata, likely guest details, topic matches, and fit scoring so you can find founders, operators, investors, and niche voices worth contacting or tracking. - **URL**: https://apify.com/soft\_but\_savage/podcast-guest-intelligence.md - **Developed by:** [Tahira Muhammad](https://apify.com/soft_but_savage) (community) - **Categories:** Developer tools, Lead generation, Social media - **Stats:** 1 total users, 0 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Podcast Guest Intelligence API Turn podcast RSS feeds into structured guest-appearance intelligence. This Actor parses podcast feeds, extracts episode metadata, identifies likely guest names, companies, and roles, and scores each episode against your topic keywords. When the RSS text is weak, it can fall back to episode-page context to recover guest details. It is built for PR teams, founder-brand operators, recruiters, sales teams, and researchers who want a cleaner workflow than manually scanning podcast apps. Best results come from interview-style feeds where guest names or roles appear in episode titles, descriptions, or episode pages. ### What you get - podcast name - episode title - episode URL - publication timestamp - likely guest name - likely guest company - likely guest role - guest confidence score - guest extraction method - page-context enrichment flag - guest count - additional guests for multi-guest episodes - matched topic keywords - topic match count - fit score - stable record ID - run summary ### Best use cases - founder and executive outreach - PR opportunity tracking - competitor media monitoring - podcast prospecting for startup and SaaS teams - research feeds for active voices in a niche ### Input ```json { "feedUrls": [ "https://anchor.fm/s/7c624c84/podcast/rss" ], "topicKeywords": ["ai", "startup", "saas", "fundraising", "founder"], "maxEpisodesPerFeed": 15, "emitOnlyMatchedTopics": false, "userAgent": "Soft But Savage research@example.com" } ```` ### Output Each dataset item is a structured guest-appearance record. The Actor is designed to help you find people, companies, and topics worth outreach or follow-up. Each record now includes: - `record_id` for stable dedupe and syncing - normalized `published_at` timestamps - `guest_confidence` and `guest_extraction_method` - `page_context_used` when episode-page enrichment was attempted - `guest_count` and `additional_guests` for episodes with multiple extracted guests - `topic_match_count` - `episode_summary` The Actor also writes a `RUN_SUMMARY` record to the default key-value store with per-feed status and counts. That summary now includes total records, records with extracted guests, high-confidence guest records, and page-enriched records. # Actor input Schema ## `feedUrls` (type: `array`): Podcast RSS feeds to analyze. ## `topicKeywords` (type: `array`): Optional keywords used to score topical fit from episode title and description. ## `maxEpisodesPerFeed` (type: `integer`): Maximum number of recent episodes to parse from each feed. ## `emitOnlyMatchedTopics` (type: `boolean`): If true, only output episodes matching at least one topic keyword. ## `userAgent` (type: `string`): User-Agent string used for feed requests. ## `openaiApiKey` (type: `string`): Optional API Key for GPT-4o inference on complex titles. ## Actor input object example ```json { "feedUrls": [ "https://anchor.fm/s/7c624c84/podcast/rss" ], "topicKeywords": [ "ai", "startup", "saas", "fundraising", "founder" ], "maxEpisodesPerFeed": 15, "emitOnlyMatchedTopics": false, "userAgent": "Soft But Savage research@example.com" } ``` # Actor output Schema ## `results` (type: `string`): No description ## `run_summary` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "feedUrls": [ "https://anchor.fm/s/7c624c84/podcast/rss" ], "topicKeywords": [ "ai", "startup", "saas", "fundraising", "founder" ], "maxEpisodesPerFeed": 15, "emitOnlyMatchedTopics": false, "userAgent": "Soft But Savage research@example.com" }; // Run the Actor and wait for it to finish const run = await client.actor("soft_but_savage/podcast-guest-intelligence").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "feedUrls": ["https://anchor.fm/s/7c624c84/podcast/rss"], "topicKeywords": [ "ai", "startup", "saas", "fundraising", "founder", ], "maxEpisodesPerFeed": 15, "emitOnlyMatchedTopics": False, "userAgent": "Soft But Savage research@example.com", } # Run the Actor and wait for it to finish run = client.actor("soft_but_savage/podcast-guest-intelligence").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "feedUrls": [ "https://anchor.fm/s/7c624c84/podcast/rss" ], "topicKeywords": [ "ai", "startup", "saas", "fundraising", "founder" ], "maxEpisodesPerFeed": 15, "emitOnlyMatchedTopics": false, "userAgent": "Soft But Savage research@example.com" }' | apify call soft_but_savage/podcast-guest-intelligence --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=soft_but_savage/podcast-guest-intelligence", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Podcast Guest Intelligence API", "description": "Track podcast guest appearances without manually scanning podcast apps. It converts podcast RSS feeds into structured records with episode metadata, likely guest details, topic matches, and fit scoring so you can find founders, operators, investors, and niche voices worth contacting or tracking.", "version": "0.1", "x-build-id": "fF8QKEqB3FZnBgee2" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/soft_but_savage~podcast-guest-intelligence/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-soft_but_savage-podcast-guest-intelligence", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/soft_but_savage~podcast-guest-intelligence/runs": { "post": { "operationId": "runs-sync-soft_but_savage-podcast-guest-intelligence", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/soft_but_savage~podcast-guest-intelligence/run-sync": { "post": { "operationId": "run-sync-soft_but_savage-podcast-guest-intelligence", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "feedUrls" ], "properties": { "feedUrls": { "title": "RSS feed URLs", "type": "array", "description": "Podcast RSS feeds to analyze.", "items": { "type": "string" } }, "topicKeywords": { "title": "Topic keywords", "type": "array", "description": "Optional keywords used to score topical fit from episode title and description.", "items": { "type": "string" } }, "maxEpisodesPerFeed": { "title": "Max episodes per feed", "minimum": 1, "maximum": 200, "type": "integer", "description": "Maximum number of recent episodes to parse from each feed.", "default": 15 }, "emitOnlyMatchedTopics": { "title": "Emit only matched topics", "type": "boolean", "description": "If true, only output episodes matching at least one topic keyword.", "default": false }, "userAgent": { "title": "User-Agent", "type": "string", "description": "User-Agent string used for feed requests.", "default": "Soft But Savage research@example.com" }, "openaiApiKey": { "title": "OpenAI API Key", "type": "string", "description": "Optional API Key for GPT-4o inference on complex titles." } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```