"How to check differences between files" matching MCP servers:

This MCP server enables Claude to speak summaries, announcements, and explanations aloud using text-to-speech — right from your terminal.

Enables transcription of local audio recordings and comparison of the resulting transcript—or two supplied texts offline—against a reference script to flag suspected omissions, additions, and substitutions.

Enables LLM agents to process local videos into timestamped, citable text documents and then query them through tools for listing videos, retrieving transcripts, and fetching specific segments, all fully offline.

Enables converting text to speech audio in 20+ languages, returning base64-encoded MP3 output via Google TTS with x402 micropayment-based pay-per-call access.

Enables AI agents to transcribe Instagram Reels into text by providing a tool that accepts a Reel URL and returns the speech transcript along with metadata such as author and duration.

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.

Enables downloading videos from platforms like YouTube and converting them to text using OpenAI Whisper and ffmpeg. It supports multiple output formats including TXT, JSON, SRT, and VTT for transcriptions.

Enables voice-driven family check-ins and safety escalation through five MCP tools over Streamable HTTP, recording check-ins, scheduling recurring reminders with grace windows, detecting missed check-ins, raising critical help alerts, and resolving them from a live dashboard. All reads and writes flow through these tools into a SQLite store, with safety rules ensuring explicit help requests override upbeat wording and never duplicate or downgrade alerts.

An MCP server that provides speech-to-text transcription and speaker diarization using OpenAI Whisper and pyannote.audio.

Enables text-to-speech conversion using Google Translate's TTS, supporting many languages and accents, and saving MP3 files.

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.

Enables agents to convert text to speech using OpenAI's TTS models with voice selection, delivery instructions, and queue-based audio playback. Supports both blocking and non-blocking modes for flexible audio generation and playback control.

An MCP server that enables voice-to-voice AI conversations using ElevenLabs for speech synthesis and recognition, with tools for voice management, text-to-speech, and speech-to-text.

Enables MCP clients such as Claude to generate spoken audio locally, narrating English with Kokoro and Malayalam with IndicF5, Parler-TTS, Piper or MMS, including cloned Malayalam voices, pronunciation lexicons, and number/currency expansion. Outputs loudness-normalised WAV or MP3 and runs long narrations through a pollable job queue so tool calls never time out.

Enables submitting audio via URL or Base64 for local Whisper transcription, then checking job status and results or deleting transcription jobs. It provides asynchronous job handling and SSRF-protected downloads/callbacks without cloud API calls.

Enables AI assistants to transcribe audio files using dTelecom's real-time speech-to-text with pay-per-use USDC micropayments, no API keys required.

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

Enables MCP clients to transcribe local audio files or public audio URLs into plain text, JSON with word timestamps, or SRT/VTT subtitles, with options to save output to a file.

Enables MCP-capable assistants to transcribe local audio files or URLs and perform speaker diarization for Spanish and Portuguese audio, with options for speaker count hints, domain prompts, and transcript retrieval in multiple formats.

Transcribes audio files by referencing them in chat, using OpenAI's speech-to-text models locally without uploading audio, and supports speaker diarization.

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

Enables Claude Desktop to generate Gemini text-to-speech audio, save .wav files locally, and manage generated audio files through MCP tools.

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 MCP clients to transcribe audio/video files locally, generate SRT subtitles, and burn captions into videos via tool calls, without a cloud API.

Enables automated audio restoration, transcription, and speaker diarization via MCP tools for queuing files, monitoring progress, and retrieving speaker-labeled transcripts.

Enables AI to analyze audio files for loudness, voice quality, and more via the AudioLab API, supporting both public URLs and local files.

Enables high-quality transcription and subtitle generation from local media files or URLs using Faster Whisper on local hardware. It supports automatic language detection and integration with MCP clients for seamless speech-to-text workflows.

Enables AI agents to send the same short audio clip to multiple speech-to-text providers and compare transcripts, CER/WER, latency, and estimated cost. It also lets agents check which providers are configured and estimate costs from a built-in price table.

Enables voice-first shared household expense tracking through Alexa+, letting flatmates record purchases, check balances, and settle debts in the fewest payments.

Enables transcription of local audio files and YouTube links in over 40 languages, including translation between supported languages and English, by calling an already-running Nemotron 3.5 Transcribe endpoint. Long recordings are automatically split at pauses and processed piece by piece, with optional speaker repetition at joins.

MCP server integrating VolcEngine for automatic speech recognition (ASR) and text-to-speech (TTS), converting audio to text or text to audio files.

Enables AI apps to transcribe local audio and video files on the user's own GPU, producing SRT/VTT subtitles and text without cloud uploads. It also helps find media files, list available devices, and list supported languages and models.

Enables Claude Code to transcribe audio and video files using the Speechmatics Batch API, with support for speaker diarization, batch processing, and searching transcripts.

Enables AI agents on macOS to securely read and search the local Messages database, catch up on missed messages via a persistent inbox, and send texts or files to allowlisted chats, with optional voice note transcription and text-to-speech.

Connects to the TypeWhisper macOS app to let coding agents transcribe local files, inspect model status, search history, and manage dictionary terms and corrections.

Enables AI assistants to transcribe audio files from URLs or local paths using AssemblyAI's services, with support for speaker diarization, language detection, and asynchronous job management through a standardized MCP interface.

Local-only transcription server for MCP agents, powered by CrispASR. Transcribes audio/video files without cloud uploads, supporting English and Chinese.

An MCP (Model Context Protocol) server that provides seamless integration between Fish Audio's Text-to-Speech API and LLMs like Claude, enabling natural language-driven speech synthesis.

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.

A stdio MCP server that enables long-form audio transcription through the NAVER Cloud CLOVA Speech API, accepting local files, trusted HTTPS URLs, or Object Storage keys with optional speaker diarization. It supports synchronous results and billable asynchronous jobs, letting clients check job status and retrieve transcripts with speaker labels and word timings alongside an offline health tool.