"semantic-release" matching MCP servers:

Voice input for Claude Code — speak Vietnamese or English; hold a hotkey, speak, release, and the transcribed text is cleaned and pasted into the input box for editing before sending.

Enables MCP clients to leverage the Intel Arrow Lake NPU for local speech transcription, screenshot OCR, private semantic search, and hardware diagnostics, all processed locally.

MCP server that turns any audio or video source into structured, searchable intelligence for agents, enabling download, transcription, semantic search, speaker identification, and more.

MCP server for OpenHAB v5+ that exposes the entire REST API as tools for AI models, enabling complete control over items, things, rules, persistence, and semantic model.

Enables AI agents to run SearXNG-powered metasearch across multiple engines and categories, with optional vector-based semantic re-ranking of results and Tavily-compatible responses. It also converts many document and media formats—including PDF, Office files, Outlook messages, and audio or YouTube recordings—into text.

An MCP server that gives AI agents the ability to listen to and understand music/audio files, enabling semantic analysis, stem separation, lyrics transcription, and signal processing via tool calls.

Enables decoding of acoustic signals such as fundamental frequency, speaking rate, jitter, and pause ratio together with semantic sentiment to infer high-dimensional emotional states and emit real-time expressive TTS prosody directives. It runs as a zero-dependency JSON-RPC 2.0 MCP server over stdio, exposing these capabilities as callable tools.

Exposes an MCP tool that fuses acoustic prosody measurements (F0, speaking rate, jitter, pause ratio) with semantic sentiment to infer high-dimensional emotional states from speech. Returns tone, speaking-rate multiplier, and pitch-shift directives so agents can drive real-time expressive TTS modulation through JSON-RPC over stdio.

Enables AI assistants to programmatically edit, analyze, and export audio projects through MCP tools, including multi-track editing, effects, transcription, and semantic search.

Enables real-time voice agents and streaming audio pipelines to detect conversational turn completion, distinguishing finished speech turns from mid-sentence hesitation pauses using acoustic VAD and semantic scoring. It provides low-latency decision and telemetry output through a native MCP interface for integration with MCP-compliant clients.