"Information about PG Vector" matching MCP servers:

Analyze an hour-long YouTube video sentence by sentence in three minutes, and extract the information you need from the screen. Open-source local MCP server for AI clients.

Gives an AI agent access to your macOS Telegram account via MTProto: it saves chats as Markdown archives, searches and summarizes them, transcribes voice messages, OCRs photos with Apple Vision, and sends messages only after your confirmation.

Enables MCP clients to place real phone calls to businesses in the US and Canada, navigating phone menus, waiting on hold, asking the agent mid-call for information, and returning structured answers with transcripts. Supports booking, quotes, cancellations, and multi-business calls in parallel.

Read-only MCP server for Telegram that enables reading messages and transcribing voice, audio, and video notes via the Telegram API for use with Codex and Claude Code.

Enables small online store owners to run a Shopify or WooCommerce shop by voice through Alexa+, answering questions about sales and stock while executing confirmation-gated actions like shipping orders or drafting supplier messages. Destructive or large-impact writes require a spoken code and are recorded in an audit log.

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.

Enables spoken questions about disease outbreaks reported to India's IDSP, returning short read-aloud answers on what's circulating, where diseases hit hardest, seasonal peaks, and trends across 16 diseases and 764 districts. It also tells users when data is too sparse to forecast instead of guessing.

A self-hosted MCP server that lets a homeowner give sitters, dog walkers, and family short spoken pass codes so whoever is home can ask Alexa+ about notes, routines, and emergencies and hear only the parts they're allowed to. Unanswered questions are routed to the owner, who replies by voice, and the answer is saved as a shared note for next time.

Enables users to prepare and conduct phone calls for errands, gathering context before dialing and looking up missing information through connected tools during the conversation.

Enables AI assistants to summarize, take notes on, and answer questions about YouTube, Bilibili, and Xiaohongshu videos by providing subtitles and local speech transcription with timestamps via MCP.

Enables parsing Douyin video information, downloading videos without watermark, and transcribing speech to text using Tencent Cloud ASR.

Enables AI agents to interact with a personal Telegram account via MCP, offering tools for reading and searching chats, summarizing unread messages, sending and editing messages, handling files and voice transcripts, and managing groups and channels, with read-only mode by default.

Enables Claude to generate local text-to-speech audio, transcribe audio/video, change voices, and manage voice packs on a Raspberry Pi 5.

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.

A self-hosted HTTP MCP server wrapping the ElevenLabs speech-to-text API, enabling audio transcription with speaker diarization.

Enables AI clients to watch local video files or YouTube/Bilibili and other supported URLs, receiving timestamped transcripts, subtitles, searchable text and keyframe contact sheets. Runs fully offline with local speech recognition and bundled ffmpeg, so no API key or cloud upload is needed.

Enables an assistant to transcribe video or podcast recordings, then read, search, summarize, and manage the resulting transcripts through MCP tools.

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 Alexa+ voice intents to be evaluated and orchestrated through AWS Bedrock Claude 3.5 Sonnet, coordinating multi-surface actions across Ring, Fire TV, and Wearable AI devices via MCP tools, prompts, and resources.

Enables AI assistants to read Bilibili, YouTube, and local videos by supplying subtitles, speech transcription, and sampled frames with timestamps, so users can ask about content, verify on-screen details, and continue with follow-up questions. Also provides a general queue and history plus a Scroll workflow that logs into a separate Bilibili account for personalized recommendations, inbox messages, forwarded videos, and authorized delivery.