"Resources and Tools for Working with Docker" 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.

An MCP server enabling video processing via natural language: transcription with Whisper, segment cutting with FFmpeg, and file management.

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.

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.

An MCP server providing tools for speech-to-text, translation, language detection, question answering, and text-to-speech using Sarvam AI models, enabling multilingual voice agents.

Provides various AI capabilities through DeepInfra's OpenAI-compatible API including image generation, text processing, embeddings, speech recognition, object detection, and classification tasks. Enables users to access multiple AI models for diverse tasks like generating images from prompts, transcribing audio, analyzing text sentiment, and performing computer vision operations.

Lets AI assistants understand what you're working on — current screen content, recent dictation, clipboard, and saved notes — running entirely on your own machine with nothing sent to the cloud.

MCP server for SpeechWeave transcription, enabling AI assistants to transcribe local files and URLs via wait-first or async tools.

MCP server that scores dialogue transcripts for bridging quality, offering per-speaker indicator scores with evidence and tools for parsing, comparing, and analyzing conversations.

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

Enables AI agents to generate speech using Gemini TTS models, with tools for text-to-speech, task polling, and pricing checks.

An MCP server for audio-to-text transcription using Google's Gemini API via OpenRouter, offering multiple tools for raw, cleaned, or formatted transcripts with support for local and remote deployment.

Enables voice input for AI coding assistants by recording audio, transcribing it locally with Whisper, and optionally typing the text at the cursor position. Supports multiple languages and works with MCP-compatible tools like OpenCode, Claude Code, and Cursor.

Enables users to convert text into high-quality audio by accessing the OpenAI Text-to-Speech API. It supports customizable model selection and voice options for synthesized speech generation via the MCP protocol.

Facilitates direct speech generation using Claude for multiple languages and emotions, integrating with a Zonos TTS setup via the Model Context Protocol.

Provides AI editors with access to Deepgram's speech-to-text transcription and audio intelligence tools. Dynamically fetches available capabilities from Deepgram's API at runtime, ensuring access to new features without package upgrades.

Enables Cursor, Claude, and other MCP agents to interact with the HyperWhisper app for voice transcription, model management, and recording search.

Remote MCP server wrapping the Bolna voice AI REST API, providing 11 tools (7 read, 4 write) for voice AI interactions.

Provides read-only access to local voice-to-text transcription history from the SayAll wireless mic app on macOS. Enables MCP-compatible assistants to query and paginate past transcripts by time and app with strong privacy boundaries.

Enables AI agents to provision phone numbers, send SMS, place AI voice calls, and react to inbound events via the Dial communication stack, all through MCP tools.