# Podcast Show Notes Generator - Auto Chapters (`ntriqpro/podcast-show-notes-mcp`) Actor Create detailed show notes and chapters for podcasts automatically. Save hours of manual work. - **URL**: https://apify.com/ntriqpro/podcast-show-notes-mcp.md - **Developed by:** [daehwan kim](https://apify.com/ntriqpro) (community) - **Categories:** MCP servers, AI, Developer tools - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per event + usage This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## 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 Show Notes MCP Server Generate structured podcast show notes, chapters, and highlights from audio. Powered by Whisper (OpenAI) and Qwen AI. No full transcript stored — only structured summaries, chapters, and key quotes. ### Features | Tool | Description | Price | |------|-------------|-------| | `generate_show_notes` | Podcast show notes with key takeaways (brief or detailed) | $0.10/use | | `generate_chapters` | Timestamped chapter markers for navigation | $0.08/use | | `extract_highlights` | Key quotes and action items (short excerpts only) | $0.12/use | ### Connect via Claude Desktop Add to your Claude Desktop MCP settings: ```json { "mcpServers": { "podcast-show-notes": { "url": "https://ntriqpro--podcast-show-notes-mcp.apify.actor/mcp?token=YOUR_APIFY_TOKEN" } } } ```` ### Supported Audio Formats MP3, WAV, M4A, OGG, FLAC, WebM, and other common podcast formats. ### Input Parameters #### generate\_show\_notes - `audioUrl` (required): URL of the podcast audio file - `style` (optional): "brief" (3-5 takeaways) or "detailed" (sections with summary). Default: "detailed" #### generate\_chapters - `audioUrl` (required): URL of the podcast audio file #### extract\_highlights - `audioUrl` (required): URL of the podcast audio file ### Output Examples #### generate\_show\_notes (detailed) ```json { "status": "success", "show_notes": { "summary": "This episode discusses quarterly business performance, highlighting new market expansion into Asia...", "sections": [ { "title": "Summary", "content": "Full summary of the episode..." } ] }, "key_takeaways": [ "Revenue growth exceeded targets by 15%", "New Asia market shows strong early adoption", "Team hiring accelerating Q3-Q4", "Product roadmap shifted to include AI features", "Budget allocation approved for R&D" ], "topics": [ "quarterly review", "market expansion", "revenue growth", "product development" ], "style": "detailed", "disclaimer": "AI-generated show notes. Not approved by or affiliated with podcast creator. For personal reference only. Do not redistribute without creator permission.", "model": "whisper + qwen3.5" } ``` #### generate\_chapters ```json { "status": "success", "chapters": [ { "timestamp": "00:00:00", "title": "Introduction" }, { "timestamp": "00:12:30", "title": "Q1 Results Review" }, { "timestamp": "00:25:45", "title": "Asia Market Expansion" }, { "timestamp": "00:38:20", "title": "Product Roadmap Update" }, { "timestamp": "00:50:00", "title": "Q&A and Closing" } ], "total_chapters": 5, "disclaimer": "AI-generated show notes. Not approved by or affiliated with podcast creator. For personal reference only. Do not redistribute without creator permission.", "model": "whisper + qwen3.5" } ``` #### extract\_highlights ```json { "status": "success", "highlights": [ { "quote": "We're seeing 40% month-over-month growth in the Asia region", "context": "Discussing new market expansion strategy..." }, { "quote": "Our team is doubling down on AI-driven features", "context": "Product roadmap update..." }, { "quote": "This quarter was our strongest quarter in company history", "context": "Reviewing quarterly financial results..." } ], "action_items": [ "Finalize Asia market expansion plan by end of Q2", "Schedule board meeting for budget approval", "Begin hiring for new R&D team", "Complete AI feature specification document" ], "speakers_estimated": 2, "disclaimer": "AI-generated show notes. Not approved by or affiliated with podcast creator. For personal reference only. Do not redistribute without creator permission.", "model": "whisper + qwen3.5" } ``` ### Important Notes #### No Full Transcript Stored - Only summaries, chapters, and key quotes (short excerpts) are returned - Full verbatim transcripts are never returned or stored - Audio is processed in real-time and not retained #### Legal Disclaimer Users are solely responsible for ensuring they have obtained all necessary consents and authorizations before submitting podcast recordings for processing. This service: - Does not store audio or generate full transcripts - Processes audio in real-time only - Returns structured summaries and insights only - Complies with privacy and copyright regulations #### Technology Stack - **Speech Recognition**: OpenAI Whisper (MIT License) - **Text Analysis**: Qwen 3.5 (Apache 2.0 License) - **Processing**: Local AI inference (no third-party data sharing) ### Licensing This service uses the following open source models: - [OpenAI Whisper](https://github.com/openai/whisper) — MIT License - [Qwen 3.5](https://huggingface.co/Qwen/Qwen3.5-4B) — Apache 2.0 License See respective repositories for full license terms. ### Use Cases - **Content Creators**: Generate show notes and chapters for podcast hosting platforms - **Researchers**: Extract key points and action items from interviews or seminars - **Podcast Listeners**: Create personal study guides from educational podcasts - **Teams**: Document meeting transcripts and action items - **Media Organizations**: Bulk process podcast catalogs for searchability Platform usage is free. You only pay per tool use (see pricing above). *** ### 🔗 Related Actors by ntriqpro Extend this actor with the ntriqpro intelligence network: - [**supply-chain-risk-mcp**](https://apify.com/ntriqpro/supply-chain-risk-mcp) — MCP server for supply chain risk - [**video-intelligence-mcp**](https://apify.com/ntriqpro/video-intelligence-mcp) — MCP server for video intelligence - [**content-factory-mcp**](https://apify.com/ntriqpro/content-factory-mcp) — MCP server for content-factory ### ⭐ Love it? Leave a Review Your rating helps professionals discover this actor. [Rate it here](https://apify.com/ntriqpro/podcast-show-notes-mcp/reviews). # Actor input Schema ## `standbyTimeout` (type: `integer`): How long (in seconds) the MCP server stays active waiting for tool calls before shutting down. Default is 300 seconds (5 minutes). Increase for long-running sessions. ## `logLevel` (type: `string`): Controls how much detail appears in the Actor log. Use 'info' for normal operation, 'debug' for troubleshooting, or 'error' for minimal output. ## Actor input object example ```json { "standbyTimeout": 300, "logLevel": "info" } ``` # Actor output Schema ## `results` (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 = { "standbyTimeout": 300, "logLevel": "info" }; // Run the Actor and wait for it to finish const run = await client.actor("ntriqpro/podcast-show-notes-mcp").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 = { "standbyTimeout": 300, "logLevel": "info", } # Run the Actor and wait for it to finish run = client.actor("ntriqpro/podcast-show-notes-mcp").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 '{ "standbyTimeout": 300, "logLevel": "info" }' | apify call ntriqpro/podcast-show-notes-mcp --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ntriqpro/podcast-show-notes-mcp", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Podcast Show Notes Generator - Auto Chapters", "description": "Create detailed show notes and chapters for podcasts automatically. Save hours of manual work.", "version": "1.0", "x-build-id": "6Oa89jNZW39yhvxA8" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ntriqpro~podcast-show-notes-mcp/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ntriqpro-podcast-show-notes-mcp", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ntriqpro~podcast-show-notes-mcp/runs": { "post": { "operationId": "runs-sync-ntriqpro-podcast-show-notes-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ntriqpro~podcast-show-notes-mcp/run-sync": { "post": { "operationId": "run-sync-ntriqpro-podcast-show-notes-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "standbyTimeout": { "title": "Standby Timeout (seconds)", "minimum": 60, "maximum": 3600, "type": "integer", "description": "How long (in seconds) the MCP server stays active waiting for tool calls before shutting down. Default is 300 seconds (5 minutes). Increase for long-running sessions." }, "logLevel": { "title": "Log Level", "enum": [ "info", "debug", "error" ], "type": "string", "description": "Controls how much detail appears in the Actor log. Use 'info' for normal operation, 'debug' for troubleshooting, or 'error' for minimal output." } } }, "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 } } } } } } } } } } ```