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    Enables shopkeepers to manage a credit ledger by voice in Hinglish—adding udhaar, recording payments, checking balances and top defaulters, drafting WhatsApp reminders, and mapping nicknames to customers.
    MIT
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    Fast MCP Telegram — Production-grade Telegram MCP server with direct MTProto API, multi-user ACL, dual transport (stdio + HTTP SSE), voice transcription, and context-optimized design. One-command setup with uvx fast-mcp-telegram
    8
    203 PyPI
    50
    MIT
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    Enables converting video and audio files into transcripts and Traditional Chinese subtitles using Groq Whisper with a pluggable translation backend, including an English-to-Chinese pipeline and a Chinese-to-Taiwanese-Mandarin proofreading pipeline. Transcriptions run as background jobs whose progress, output subtitle paths, and setup status can be queried through the conversation.
    4
    MIT
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    Turns Claude or ChatGPT into a live system design interviewer that watches a hand-drawn whiteboard, reads the diagram as structured data or an image, hears spoken answers, pins questions on components, and grades the session. Everything runs locally, so users can practice mock interviews on their own machine without API keys.
    13
    109 npm
    1
    MIT
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    Enables access to a backend's native MCP tools and broader HTTP API for speech generation, voice cloning/design, transcription, dubbing, translation, subtitles, audiobooks, and related batch/long-form workflows over Streamable HTTP or local stdio.
    21
    AGPL 3.0
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    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.
    Apache 2.0
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    Enables Claude to run a structured learning program by selecting topics, delivering lectures to a local site, reading and grading answers, tracking progress, and closing completed topics. It also serves a localhost website for viewing the curriculum and progress.
    MIT
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    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.
    MIT
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    Enables proactive voice assistance for flight disruptions, including alerts, rebooking, refund eligibility and requests, bag status, accessibility assistance, and stranded-traveler support through MCP tools, subscriptions, and approval-based elicitation.
    MIT
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    Enables voice-first assistants to answer small-business compliance questions for Idaho and New Mexico LLCs, returning short spoken checklists, the next filing deadline, plain-language explanations of terms, and quick website accessibility checks. Every fee and rule is cited to a statute or official source, and unsupported states or unverified details are labeled unknown.
    MIT
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    Generate realistic text-to-speech locally on Apple silicon with Fish Audio's Drama 3 through a stdio MCP server, including voice cloning, voice design, and directed retakes. Requires Drama Studio running on a Mac; speech generation uses Metal and Core ML.
    4
    Apache 2.0
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    Enables agents to discover devices, query their capabilities, invoke system calls, and stage resources or deliver apps to connected WishOS hardware through a self-hosted connector and relay. It routes device-initiated tasks into an existing harness session (Codex, Claude Code, and others), keeping inference, tools, and history with that agent while handling voice, interface, and app transfer to the device.
    MIT
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    Self-hosted WhatsApp management over Model Context Protocol, exposing a streamable HTTP MCP endpoint with 30 tools for session/QR pairing, messaging, media storage, and optional on-CPU voice note transcription via whisper.cpp.
    MIT
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    Enables voice assistants to screen voicemail transcripts for scam risk, returning a verdict with plain spoken reasons and suggested actions. Callers can then be blocked or reported through a two-step stage-and-approve flow that requires an explicit spoken confirmation.
    MIT
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    vidlizer pulls frames out of any video, image, or PDF using ffmpeg, sends them to a vision LLM, and returns a flow array — one entry per scene. Each entry tells you what happened, who was on screen, what text was visible, and what changed. If the video has audio, it transcribes it with Apple MLX Whisper and merges the speech into each step.
    25 PyPI
    4
    MIT