# AI Meeting Assistant - Transcribe & Summarize (`ntriqpro/meeting-notes-mcp`) Actor Turn meeting recordings into notes automatically: transcribe Zoom, Teams, Meet, MP3 or MP4 audio with speaker diarization, then extract a summary, decisions and action items as structured JSON. Runs as an MCP server an AI agent can call directly. - **URL**: https://apify.com/ntriqpro/meeting-notes-mcp.md - **Developed by:** [daehwan kim](https://apify.com/ntriqpro) (community) - **Categories:** MCP servers, AI, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 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/actors/running/actors-in-store.md#pay-per-event ## What's an Apify Actor? Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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. - **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use). - **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`. - **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`. - **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`. - **Any other language** — 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 ## Meeting Notes MCP AI-powered meeting transcription, summarization with action items, and speaker analysis using OpenAI Whisper and Qwen. ### Features Meeting Notes MCP is an MCP (Model Context Protocol) server that provides three powerful tools for processing meeting audio: 1. **Transcribe Meeting** ($0.08/call) - Convert audio to text with timestamps - Support for multiple languages (English, Korean, etc.) - Segment-based output for easy navigation 2. **Summarize Meeting** ($0.10/call) - Generate concise or detailed meeting summaries - Extract action items automatically - Powered by Qwen 3.5 LLM 3. **Analyze Meeting** ($0.12/call) - Estimate number of speakers - Identify key topics discussed - Detect overall sentiment - Extract important phrases ### Powered By - **OpenAI Whisper** (MIT License) — State-of-the-art speech recognition - **Qwen 3.5** (Apache 2.0 License) — Advanced language model for summarization and analysis - **ntriq Local AI** — Secure on-premises AI inference ### How to Use #### Connect to Claude Desktop Add to your Claude Desktop configuration: ```json { "mcpServers": { "meeting-notes": { "url": "https://ntriqpro--meeting-notes-mcp.apify.actor/mcp?token=YOUR_APIFY_TOKEN" } } } ``` #### Standby Mode Get the Standby URL from Apify and use with HTTP requests: ```bash curl -X POST "https://ntriqpro--meeting-notes-mcp.apify.actor/mcp?token=$APIFY_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "jsonrpc": "2.0", "id": 1, "method": "tools/call", "params": { "name": "transcribe_meeting", "arguments": { "audio_url": "https://example.com/meeting.mp3" } } }' ``` ### API Reference #### Tool: transcribe\_meeting Transcribe audio to text with timestamps. **Input:** - `audio_url` (string, required) — URL of audio file - `language` (string, optional) — Language code (e.g., "en", "ko") **Output:** ```json { "status": "success", "data": { "text": "Full meeting transcript...", "segments": [ { "start": 0, "end": 5.5, "text": "Opening statement...", "confidence": 0.98 } ], "language": "en" }, "model": "whisper-1", "metadata": { "endpoint": "/audio/transcribe", "timestamp": "2026-03-29T10:30:00Z", "inputUrl": "..." } } ``` #### Tool: summarize\_meeting Generate meeting summary with optional action items. **Input:** - `audio_url` (string, required) — URL of audio file - `summary_type` (enum, default: action\_items) — Type of summary: - `"brief"` — One-paragraph summary - `"detailed"` — Multi-paragraph with sections - `"action_items"` — Focus on action items and decisions **Output:** ```json { "status": "success", "data": { "transcript": "Full transcript...", "summary": "Meeting summary...", "summaryType": "action_items", "actionItems": [ { "item": "Implement new API endpoint", "owner": "John", "dueDate": "2026-04-05" } ] }, "model": "qwen-3.5", "metadata": { "endpoint": "/audio/summarize", "timestamp": "2026-03-29T10:30:00Z", "summaryType": "action_items" } } ``` #### Tool: analyze\_meeting Full meeting analysis with speakers, topics, sentiment. **Input:** - `audio_url` (string, required) — URL of audio file **Output:** ```json { "status": "success", "data": { "speakersEstimated": 3, "topics": [ "Product roadmap", "Q2 goals", "Team expansion" ], "sentiment": "positive", "keyPhrases": [ "launch timeline", "resource allocation", "customer feedback" ], "summary": "Executive summary of the meeting..." }, "model": "qwen-3.5", "metadata": { "endpoint": "/audio/analyze", "timestamp": "2026-03-29T10:30:00Z" } } ``` ### Pricing Free plan: each run answers up to 25 billable tool calls (up to 25 results). Paid Apify plans receive the full result set. Pay-per-event model. Charges are deducted per successful API call: | Tool | Price | |------|-------| | transcribe\_meeting | $0.08 | | summarize\_meeting | $0.10 | | analyze\_meeting | $0.12 | No charges for failed calls or errors. ### Error Handling All tools return consistent error format: ```json { "status": "error", "error": "Error message describing what went wrong" } ``` Common errors: - Timeout (>120 seconds) — "Transcription timeout (exceeded 120 seconds)" - Invalid URL — "HTTP 404: Audio file not found" - Network failure — "Connection refused" ### Supported Audio Formats The underlying service supports: - MP3, WAV, FLAC, OGG - Maximum file size: 500 MB - Maximum duration: 24 hours ### Requirements - Node.js 18.0 or higher - Internet connection to ai.ntriq.co.kr - Valid Apify account for standby mode ### Health Check ```bash curl https://ntriqpro--meeting-notes-mcp.apify.actor/health ``` Response: ```json { "status": "ok", "service": "meeting-notes-mcp", "version": "1.0.0", "timestamp": "2026-03-29T10:30:00.000Z" } ``` ### License This MCP server is provided under the MIT License. The underlying models use: - OpenAI Whisper (MIT License) - Qwen Model (Apache 2.0 License) ### Support For issues or questions: 1. Check the `/health` endpoint 2. Review error messages in stdout logs 3. Verify audio URL accessibility 4. Contact support@ntriq.co.kr *** **Made with** by ntriq Engineering Team. Powered by [Apify](https://apify.com) and [Claude](https://claude.ai). *** ### 🔗 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/meeting-notes-mcp/reviews). ### Disclaimer **GENERAL DISCLAIMER**: This is an AI-powered tool. Output may contain errors, inaccuracies, or omissions. Do not rely on output for legal, medical, or financial decisions without independent professional review. We provide no warranty, express or implied, regarding the accuracy, completeness, or fitness for any particular purpose of the generated output. # 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. Free plan: each run answers up to 25 billable tool calls. Paid Apify plans receive the full result set. ## `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/meeting-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/meeting-notes-mcp").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).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/meeting-notes-mcp --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,ntriqpro/meeting-notes-mcp" } } } ``` The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer ` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations). ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/YQ39G87AQb38xmTwh/builds/7S09DnORFfGnBpycd/openapi.json