"A service for predicting triathlon results based on training data" matching MCP servers:

Self-host a realtime voice-call companion for coding agents. Exposes an MCP endpoint that agents can poll as an alternate input stream.

Official MCP server for Theta EdgeCloud's On-Demand Model APIs, providing access to 20+ AI models including image generation, audio transcription, and LLMs, directly from MCP-compatible clients.

Enables AI agents to synthesize and play short summaries aloud while keeping full answers on screen, with queued speech and stop control using online natural voices or offline synthesis.

Enables voice assistants to find nearby service providers, connect users to live video representatives for natural conversation, and handle appointment booking. It also returns confirmed bookings so the assistant can add them to its calendar.

Provides voice recognition and text extraction capabilities with support for both stdio and MCP modes, processing audio files or base64 encoded data and returning structured results with language, emotion, and speaker information.

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.

Enables Alexa+ to run spoken mock technical interviews by parsing a candidate's resume and target job description, generating tailored questions, and scoring each answer against Bar Raiser rubrics via Amazon Bedrock. It also produces a session report with score breakdowns, weak topics, and a concrete practice plan.

Enables MCP-capable chat clients to synthesize speech from text, convert it with a local RVC voice model, and render the result in an inline audio player.

Enables AI clients to watch and hear videos from local files or YouTube, Vimeo, and Loom links by returning timestamped key frames, a transcript, a contact sheet, and a combined timeline, with all processing done locally.

MCP server for local speech-to-text using Whisper Large V3 (MLX), enabling audio transcription with text/timestamps/SRT output and LLM-based correction, all running offline on Apple Silicon.

Pay-per-call x402 APIs for AI agents: DeFi token safety (honeypot/tax simulation, A-F grade), EVM chain data, web access (markdown/screenshot/PDF), speech-to-text. USDC on Base, no account, no API key

Enables MCP clients to fetch supported languages and limitations, assess pronunciation from audio against reference text in ten languages, and explain returned assessment results locally.

Enables spoken conversations with Claude on a Mac: Claude speaks through speakers, listens to the user's natural replies, and transcribes them locally. No audio leaves the computer, and it includes tools for voice setup and a hands-free voice mode.

Enables AI agents to generate spoken audio locally on a GPU via the Chatterbox models, with zero-shot voice cloning from reference clips, multilingual output, and sentence-aligned chunking for long text.

Enables AI agents to interact with the ParrotScribe transcription service on macOS, providing tools to start/stop transcription, retrieve real-time and historical transcripts, and search across sessions.

Local, private audio transcription MCP server enabling AI agents to transcribe audio files entirely on-device without uploading data.

Enables any MCP client to start, poll, and stop microphone recordings from within a conversation, returning the accumulating transcript on demand. All transcription runs locally on-device, so no audio leaves the machine.

Provides programmatic access to Apple Voice Memos on macOS, enabling AI assistants to list, retrieve details, get audio, and transcribe recordings.

Lets AI assistants query available voices from an OpenAI-compatible TTS service and synthesize text into audio with a chosen voice, tone, and speed, returning a public audio URL instead of Base64 data.

Text-to-speech MCP server that enables AI assistants to read text aloud on the user's computer using Windows SAPI, with no API key or cloud service required.