"Non-Docker Implementation of Jira with MCP" matching MCP servers:

Enables chat-driven audio analysis and enhancement using local Claude, including denoising, EQ, compression, and loudness normalization, with an A/B viewer for synchronized comparison.

Enables agents to access OpenAI-compatible transcription, live ASR, text-to-speech, voice cloning, phoneme recognition, and server-side file staging through streamable HTTP MCP tools.

Enables AI agents to perform comprehensive audio processing—stem separation, analysis, transcription, restoration, speech processing, and generation—through a unified self-hosted API with asynchronous jobs and webhooks.

Enables hands-free voice collaboration with a coding agent: you speak requirements aloud and hear only short, plain-language progress and completion summaries while the agent edits code, runs tests, and fixes bugs in the background. It also handles continuous speech recognition with automatic turn detection, barge-in interruption, and spoken approval prompts before risky operations.

Provides AI tools with transcripts of any YouTube video, including videos without captions via AI speech-to-text, with language selection and length capping.

Enables AI agents to speak using MacOS native text-to-speech, with support for blocking and non-blocking speech and a sequential queue.

Enables MCP clients such as Claude Code, Cursor, and VS Code to generate speech through three MiMo TTS models: nine built-in voices (with singing and style/audio tags), voices designed purely from a text description, and voices cloned from a local mp3/wav sample. Audio is streamed and written only inside a sandboxed output directory, with non-overwriting filenames.

Enables real-time transcription and heuristic vocal stress analysis of live financial webcasts, providing an LLM with rolling transcripts and a stress score.

Provides local audio transcription using whisper.cpp, supporting multiple models and audio formats. Enables transcription of audio files via MCP tools with optional timestamps.

Local-first CLI + MCP server for meeting recordings - Whisper transcription,

A Node.js server that enables AI assistants to interact with Bouyomi-chan's text-to-speech functionality through Model Context Protocol (MCP), allowing for voice reading of text with adjustable parameters.

A MCP server that enables transcription of audio files using OpenAI's Speech-to-Text API, with support for multiple languages and file saving options.

Best VoiceAI White Label Platform for Agencies with Full MCP Connectivity to Any Platform for Custom VoiceAi & AI Chat Integrations and You Keep 100% of the Profits

Enables creating and managing ElevenLabs conversational AI agents with an interactive UI, voice selection, and configuration of agent behavior.

Enables driving a Claude Code session directly from WhatsApp over a linked device or the official Cloud API, with bidirectional messaging, media attachments, local voice transcription, per-group personalities, and context recovery after restarts. Adds pairing-code access control, allowlists and group policies, plus remote approval or denial of tool permission prompts via emoji reactions — no API keys, no Docker.

Enables users to run and control Claude Code from Telegram around the clock, with two-way voice notes, persistent memory across restarts, scheduled reminders, and a live view of each tool call as it runs.

Enables running Claude Code around the clock through Telegram, with voice notes exchanged in both directions, a self-healing daemon that keeps sessions alive, memory and history preserved across restarts, and a live view of every tool call as it happens.

Enables asynchronous transcription of long audio and video files using Deepgram's Speech-to-Text API with features like speaker diarization, sentiment analysis, topic detection, and summarization without timeout issues.

Enables local, offline, CPU-only transcription of video/audio into timestamped SRT subtitles with Whisper, Chinese TTS dubbing (including multi-speaker dialogue), and synthesis of a new dubbed video in a single command. Supports dubbing silent videos, translating and re-voicing foreign-language videos, and batch-adding narration to short clips within AI workflows.

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.