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Implements the MCP protocol's resource subscription model to push transcribed text segments as they become available, with support for streaming audio input from system audio devices or network sources.","intents":["I want Claude to listen to live audio and transcribe it in real-time for analysis or note-taking","I need to pipe system audio or microphone input into an LLM conversation without manual copy-paste","I want to build an agent that reacts to spoken input as it's being transcribed"],"best_for":["developers building voice-enabled LLM agents","teams creating accessibility tools that bridge speech and text","builders prototyping voice-first AI applications"],"limitations":["Requires local audio device access or network audio stream — no cloud-based audio ingestion","Transcription accuracy depends on underlying speech-to-text engine (not specified in package metadata)","MCP resource model means clients must actively subscribe; no automatic broadcast to multiple clients","No built-in support for multi-language detection or speaker diarization"],"requires":["Node.js 16+ (MCP server runtime)","MCP client implementation (Claude Desktop, custom MCP client, or compatible tool)","System audio permissions or network audio stream access","Speech-to-text backend (likely Web Speech API, Whisper, or similar — not specified)"],"input_types":["audio stream (PCM, WAV, or system audio device)","network audio source"],"output_types":["text (transcribed segments)","structured JSON (transcript metadata with timestamps)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-modelcontextprotocolserver-transcript__cap_1","uri":"capability://tool.use.integration.mcp.resource.streaming.for.audio.segments","name":"mcp-resource-streaming-for-audio-segments","description":"Implements MCP's resource streaming interface to deliver transcribed audio segments incrementally to clients as they complete. Uses the MCP protocol's resource URI scheme and subscription mechanism to manage client connections, handle backpressure, and ensure reliable delivery of transcript chunks without requiring clients to poll or manage connection state.","intents":["I want transcription updates pushed to my LLM client as soon as they're available, not batched","I need to handle multiple concurrent transcription streams from different audio sources","I want the transcript to flow naturally into my agent's context without manual refresh"],"best_for":["MCP client developers integrating live transcription","teams building real-time collaborative transcription tools","developers needing low-latency audio-to-text pipelines"],"limitations":["MCP resource model is request-response based; true server-initiated push requires client polling or WebSocket upgrade (not standard MCP)","No built-in buffering or replay — clients that disconnect lose prior transcript segments unless explicitly stored","Resource URI design and subscription semantics depend on MCP server implementation details (not documented in package)"],"requires":["MCP protocol version 1.0+ (or compatible)","MCP client with resource subscription support","Node.js 16+"],"input_types":["MCP resource subscription request (JSON)"],"output_types":["MCP resource response with streaming transcript (text/plain or application/json)"],"categories":["tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-modelcontextprotocolserver-transcript__cap_2","uri":"capability://automation.workflow.system.audio.device.capture.and.forwarding","name":"system-audio-device-capture-and-forwarding","description":"Captures audio from system audio devices (microphone, line-in, or virtual audio devices) and forwards it to the transcription engine. Handles audio format negotiation, sample rate conversion, and device enumeration to allow users to select input sources. Likely uses Node.js audio libraries (e.g., node-portaudio, naudiodon) to interface with OS-level audio APIs.","intents":["I want to transcribe my microphone input without manually recording and uploading files","I need to select which audio device to transcribe from (e.g., mic vs. system audio)","I want continuous transcription of ambient audio in my office for meeting notes"],"best_for":["solo developers building voice-enabled tools","teams creating in-office transcription solutions","accessibility tool builders"],"limitations":["Requires OS-level audio driver support and permissions (may fail on restricted systems or containers)","Audio quality and transcription accuracy depend on microphone hardware and ambient noise","No built-in noise suppression or audio preprocessing — raw audio is forwarded to transcription engine","Device enumeration may differ across Windows, macOS, and Linux"],"requires":["Node.js 16+","Native audio library bindings (e.g., portaudio, ALSA on Linux)","Microphone or audio input device","OS-level audio permissions"],"input_types":["system audio device (PCM stream)"],"output_types":["audio buffer (PCM or WAV format)"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-modelcontextprotocolserver-transcript__cap_3","uri":"capability://data.processing.analysis.audio.format.normalization.and.resampling","name":"audio-format-normalization-and-resampling","description":"Normalizes incoming audio streams to a standard format (likely 16-bit PCM at 16kHz) required by the transcription engine. Handles sample rate conversion, bit depth adjustment, and channel mixing (stereo to mono) transparently. Uses audio resampling algorithms to maintain quality during format conversion without requiring client-side preprocessing.","intents":["I want to transcribe audio from different sources without worrying about format compatibility","I need the server to handle sample rate mismatches automatically","I want to reduce bandwidth by downsampling high-quality audio before transcription"],"best_for":["developers integrating multiple audio sources","teams with heterogeneous audio hardware","builders optimizing for bandwidth or latency"],"limitations":["Resampling introduces ~10-50ms latency depending on algorithm and buffer size","Quality loss is inevitable when downsampling high-quality audio (e.g., 48kHz to 16kHz)","No adaptive bitrate or dynamic format selection — uses fixed target format"],"requires":["Node.js 16+","Audio resampling library (likely libsamplerate or similar)"],"input_types":["audio buffer (any PCM format, sample rate, or bit depth)"],"output_types":["normalized audio buffer (16-bit PCM at 16kHz)"],"categories":["data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-modelcontextprotocolserver-transcript__cap_4","uri":"capability://tool.use.integration.transcription.engine.abstraction.and.provider.selection","name":"transcription-engine-abstraction-and-provider-selection","description":"Abstracts the underlying speech-to-text engine behind a provider interface, allowing selection of different transcription backends (e.g., Web Speech API, Whisper, Google Cloud Speech-to-Text, Azure Speech Services). Likely implements a plugin or strategy pattern to swap transcription providers without changing server code. Handles API authentication, error handling, and fallback logic.","intents":["I want to use a local transcription model (Whisper) instead of cloud APIs for privacy","I need to switch transcription providers without redeploying the server","I want fallback transcription if my primary provider is unavailable"],"best_for":["teams with privacy requirements (local transcription)","developers building multi-provider transcription systems","builders optimizing for cost or latency"],"limitations":["Provider abstraction adds ~50-200ms latency per transcription request due to interface overhead","Not all providers support identical features (e.g., speaker diarization, language detection) — abstraction may hide provider-specific capabilities","Fallback logic requires manual configuration and testing per provider combination"],"requires":["Node.js 16+","At least one transcription provider (local Whisper, Web Speech API, or cloud API key)"],"input_types":["audio buffer (normalized PCM)"],"output_types":["transcript text with optional metadata (confidence scores, timestamps)"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-modelcontextprotocolserver-transcript__cap_5","uri":"capability://automation.workflow.transcript.segment.buffering.and.delivery.timing","name":"transcript-segment-buffering-and-delivery-timing","description":"Buffers transcribed text segments and manages delivery timing to MCP clients, balancing latency (pushing segments as soon as available) with throughput (batching small segments to reduce overhead). Implements configurable buffering strategies (e.g., time-based, size-based, or confidence-based) to control when transcript chunks are sent to clients. Handles partial transcripts (interim results) vs. final transcripts.","intents":["I want to see transcription results as soon as they're available, even if incomplete","I need to batch small transcript segments to reduce network overhead","I want to distinguish between interim (uncertain) and final (confirmed) transcription results"],"best_for":["developers building real-time transcription UIs","teams optimizing for low-latency agent responses","builders managing bandwidth-constrained environments"],"limitations":["Buffering introduces configurable latency (typically 100-500ms) to batch segments","Interim results may be inaccurate and require correction when final results arrive","No built-in deduplication — clients must handle duplicate segments if buffering strategy changes"],"requires":["Node.js 16+","Transcription engine that supports interim results (not all providers do)"],"input_types":["transcript segment (interim or final, with confidence metadata)"],"output_types":["buffered transcript chunk (text with metadata: interim flag, timestamp, confidence)"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-modelcontextprotocolserver-transcript__cap_6","uri":"capability://tool.use.integration.mcp.server.lifecycle.and.resource.management","name":"mcp-server-lifecycle-and-resource-management","description":"Manages MCP server initialization, shutdown, and resource cleanup. Implements MCP server protocol handshake, handles client connections and disconnections, and ensures graceful shutdown of audio capture and transcription pipelines. Likely uses MCP SDK for Node.js to handle protocol details and resource registration.","intents":["I want the transcription server to start and stop cleanly without hanging processes","I need to handle multiple concurrent MCP client connections","I want proper cleanup of audio devices and transcription resources on shutdown"],"best_for":["developers deploying MCP servers in production","teams running transcription services 24/7","builders integrating with Claude Desktop or other MCP hosts"],"limitations":["MCP protocol requires synchronous resource registration at startup — dynamic resource addition not supported","No built-in load balancing for multiple concurrent transcription streams","Resource cleanup depends on proper client disconnection signals — abrupt client termination may leak audio device handles"],"requires":["Node.js 16+","@modelcontextprotocol/sdk (MCP SDK for Node.js)","MCP host (Claude Desktop, custom client, etc.)"],"input_types":["MCP protocol messages (JSON-RPC)"],"output_types":["MCP protocol responses (JSON-RPC)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":25,"verified":false,"data_access_risk":"moderate","permissions":["Node.js 16+ (MCP server runtime)","MCP client implementation (Claude Desktop, custom MCP client, or compatible tool)","System audio permissions or network audio stream access","Speech-to-text backend (likely Web Speech API, Whisper, or similar — not specified)","MCP protocol version 1.0+ (or compatible)","MCP client with resource subscription support","Node.js 16+","Native audio library bindings (e.g., portaudio, ALSA on Linux)","Microphone or audio input device","OS-level audio permissions"],"failure_modes":["Requires local audio device access or network audio stream — no cloud-based audio ingestion","Transcription accuracy depends on underlying speech-to-text engine (not specified in package metadata)","MCP resource model means clients must actively subscribe; no automatic broadcast to multiple clients","No built-in support for multi-language detection or speaker diarization","MCP resource model is request-response based; true server-initiated push requires client polling or WebSocket upgrade (not standard MCP)","No built-in buffering or replay — clients that disconnect lose prior transcript segments unless explicitly stored","Resource URI design and subscription semantics depend on MCP server implementation details (not documented in package)","Requires OS-level audio driver support and permissions (may fail on restricted systems or containers)","Audio quality and transcription accuracy depend on microphone hardware and ambient noise","No built-in noise suppression or audio preprocessing — raw audio is forwarded to transcription engine","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.24,"ecosystem":0.3,"match_graph":0.25,"freshness":0.6,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:23.904Z","last_scraped_at":"2026-05-03T14:23:43.924Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=npm-modelcontextprotocolserver-transcript","compare_url":"https://unfragile.ai/compare?artifact=npm-modelcontextprotocolserver-transcript"}},"signature":"ekV7IaKr1DWv2C5OFaNYZEGlhy9qe00aTXedC6vjPUsBoiYyax3UMXPb+KHrc6xh2nL+677AZd86OlWdtCApCA==","signedAt":"2026-06-21T04:22:22.789Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/npm-modelcontextprotocolserver-transcript","artifact":"https://unfragile.ai/npm-modelcontextprotocolserver-transcript","verify":"https://unfragile.ai/api/v1/verify?slug=npm-modelcontextprotocolserver-transcript","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}