"Tools for extracting structured data from web pages for LLM use" matching MCP servers:

Enables coding agents to watch and analyze videos by extracting scene-aware frames, transcribing speech, and generating shot timelines, all constrained by a token budget to fit LLM context limits.

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 Claude Code to leverage Chinese LLMs for multimodal tasks including image analysis, audio transcription, and deep synthesis via MCP protocol.

Local MCP server for agents to search, structure, and export authorized WhatsApp Web conversations. Uses Playwright for DOM interaction, supports message search, export, media transcription, and controlled message 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.

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

Enables room agents to generate or edit images (published directly into the room's Docs rather than passed through the model's context) and transcribe audio attachments, using the deployment's media providers with the room itself acting as the credential.

A FastMCP server that exposes a locally-hosted llama.cpp LLM as MCP tools, plus utilities for weather, news, web fetching, file I/O, and more. Enables MCP-compatible clients to use a local GGUF model for text generation without external APIs.

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.

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.

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 AI models like Claude to easily access and utilize subtitle data from YouTube videos by extracting transcripts from video URLs with support for multiple languages.

Enables AI agents to read public Instagram Reels without logging in, returning details, on-device timestamped speech-to-text transcripts, real video frames, preview comments, and Reel links harvested from web pages.

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 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.

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

SeaMeet MCP connects Claude, Cursor, Codex, and other AI agents to SeaMeet meeting recordings, transcripts, AI summaries, screenshots, action items, webhooks, and desktop recording controls. Use it to search meeting memory, read synced cloud recordings, and automate meeting notes through the Model Context Protocol.