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20 Best GitHub MCP Servers: compared and ranked, October 2026Ranked from 1,950 matching servers on stars, growth, downloads and maintenance. Updated .

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    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.
    MIT
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    D
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    MCP server for Chamade — a voice and chat gateway that lets your AI agent join meetings and DMs on Discord, Microsoft Teams, Google Meet, Telegram, SIP, Zoom, Nextcloud Talk, Slack, and WhatsApp.
    55 npm
    MIT
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    B
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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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    C
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    Enables ChatGPT on the web to generate and play spoken audio through an embedded player, exposing a speak tool that renders text with selectable styles and scenes via configurable text-to-speech providers. It routes each request across ElevenLabs, Cartesia, Azure Speech, and DashScope in a configured failover order, picking providers by language and scenario.
    15 npm
    MIT
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    C
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    Enables MCP clients to place, monitor, and hang up phone calls through authenticated tools, retrieve transcripts, and exchange correlated task results with a waiting host. It supports simulated or live calling with persisted call lifecycle records, duration limits, and idempotent requests.
    MIT
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    C
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    Enables Alexa+ to coordinate a household through 14 MCP tools: it tracks family members, auto-assigns and completes chores by workload, adds calendar events while reporting clashes, rotates pickup duty, manages a grocery list, and returns a spoken morning briefing with reasoning for every decision.
    MIT
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    A
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    Enables AI agents to ring or text a user's actual iPhone, read a question or update aloud, and return the spoken answer back to the agent as text. Calls and messages land in a single titled thread per agent, with tools for polling results, waiting for replies, and labeling conversations.
    23
    MIT
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    Enables chat-driven audio analysis and enhancement using local Claude, including denoising, EQ, compression, and loudness normalization, with an A/B viewer for synchronized comparison.
    1
    MIT
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    C
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    Enables an AI agent to read and send real iMessages—including text, voice notes, stickers, links, images, and reactions—through a managed cloud phone line without needing a Mac.
    1 npm
    AGPL 3.0
  • A
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    A
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    A stdio MCP server that lets Claude Code sessions be driven directly from WhatsApp chats, with bidirectional messaging and media, voice-note transcription, pairing-code access control, per-group personalities, and emoji-reaction approval of tool requests. It supports both linked-device pairing for personal numbers and the official WhatsApp Cloud API for business DMs, and can also be run by other MCP clients on a poll-based basis.
    MIT
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    C
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    An MCP server for AI voice synthesis with an inline audio player, allowing users to give their AI assistant a custom cloned voice using DashScope or ElevenLabs.
    MIT
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    C
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    Enables AI assistants to synthesize speech using a custom cloned voice through MiniMax TTS and present it in an inline audio player with waveform visualization and transcript controls.
    15 npm
    MIT
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    B
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    Enables an assistant to turn any video ffmpeg can read into a text transcript by extracting the audio, splitting it on silence, and transcribing each piece on-device through utt. Exposes tools to start a transcription job with optional hints and timestamps, and to poll for a transcript that is still being worked on.
    3 npm
    MIT
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    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.
    MIT
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    A self-hosted MCP server over Streamable HTTP that lets a voice assistant query production records, capture persistent shift handovers, and run container-load calculations against synthetic factory data. It enables plant managers and line operators to inspect and update shift state through natural language without any cloud dependency.
    MIT