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    MiniMax Releases MMX-CLI: A Command-Line Interface That Offers AI Brokers Native Entry to Picture, Video, Speech, Music, Imaginative and prescient, and Search

    Naveed AhmadBy Naveed Ahmad13/04/2026Updated:13/04/2026No Comments5 Mins Read
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    MiniMax, the AI analysis firm behind the MiniMax omni-modal mannequin stack, has launched MMX-CLI — Node.js-based command-line interface that exposes the MiniMax AI platform’s full suite of generative capabilities, each to human builders working in a terminal and to AI brokers working in instruments like Cursor, Claude Code, and OpenCode.

    What Downside Is MMX-CLI Fixing?

    Most giant language mannequin (LLM)-based brokers right now are sturdy at studying and writing textual content. They will purpose over paperwork, generate code, and reply to multi-turn directions. However they don’t have any direct path to generate media — no built-in approach to synthesize speech, compose music, render a video, or perceive a picture and not using a separate integration layer such because the Mannequin Context Protocol (MCP).

    Constructing these integrations usually requires writing customized API wrappers, configuring server-side tooling, and managing authentication individually from no matter agent framework you’re utilizing. MMX-CLI is positioned as a substitute strategy: expose all of these capabilities as shell instructions that an agent can invoke straight, the identical method a developer would from a terminal — with zero MCP glue required.

    The Seven Modalities

    MMX-CLI wraps MiniMax’s full-modal stack into seven generative command teams — mmx textual content, mmx picture, mmx video, mmx speech, mmx music, mmx imaginative and prescient, and mmx search — plus supporting utilities (mmx auth, mmx config, mmx quota, mmx replace).

    • The mmx textual content command helps multi-turn chat, streaming output, system prompts, and JSON output mode. It accepts a --model flag to focus on particular MiniMax mannequin variants akin to MiniMax-M2.7-highspeed, with MiniMax-M2.7 because the default.
    • The mmx picture command generates photographs from textual content prompts with controls for facet ratio (--aspect-ratio) and batch rely (--n). It additionally helps a --subject-ref parameter for topic reference, which permits character or object consistency throughout a number of generated photographs — helpful for workflows that require visible continuity.
    • The mmx video command makes use of MiniMax-Hailuo-2.3 as its default mannequin, with MiniMax-Hailuo-2.3-Quick obtainable as a substitute. By default, mmx video generate submits a job and polls synchronously till the video is prepared. Passing --async or --no-wait modifications this conduct: the command returns a job ID instantly, letting the caller test progress individually through mmx video job get --task-id. The command additionally helps a --first-frame flag for image-conditioned video era, the place a selected picture is used because the opening body of the output video.
    • The mmx speech command exposes text-to-speech (TTS) synthesis with greater than 30 obtainable voices, velocity management, quantity and pitch adjustment, subtitle timing knowledge output through --subtitles, and streaming playback help through pipe to a media participant. The default mannequin is speech-2.8-hd, with speech-2.6 and speech-02 as alternate options. Enter is capped at 10,000 characters.
    • The mmx music command, backed by the music-2.5 mannequin, generates music from a textual content immediate with fine-grained compositional controls together with --vocals (e.g. "heat male baritone"), --genre, --mood, --instruments, --tempo, --bpm, --key, and --structure. The --instrumental flag generates music with out vocals. An --aigc-watermark flag can be obtainable for embedding an AI-generated content material watermark within the output audio.
    • mmx imaginative and prescient handles picture understanding through a vision-language mannequin (VLM). It accepts a neighborhood file path or distant URL — robotically base64-encoding native information — or a pre-uploaded MiniMax file ID. A --prompt flag enables you to ask a selected query in regards to the picture; the default immediate is "Describe the picture."
    • mmx search runs an online search question by means of MiniMax’s personal search infrastructure and returns ends in textual content or JSON format.

    Technical Structure

    MMX-CLI is written virtually fully in TypeScript (99.8% TS) with strict mode enabled, and makes use of Bun because the native runtime for improvement and testing whereas distributing to npm for compatibility with Node.js 18+ environments. Configuration schema validation makes use of Zod, and backbone follows an outlined priority order — CLI flags → atmosphere variables → ~/.mmx/config.json → defaults — making deployment easy in containerized or CI environments. Twin-region help is constructed into the API shopper layer, routing World customers to api.minimax.io and CN customers to api.minimaxi.com, switchable through mmx config set --key area --value cn.

    Key Takeaways

    • MMX-CLI is MiniMax’s official open command-line interface that offers AI brokers native entry to seven generative modalities — textual content, picture, video, speech, music, imaginative and prescient, and search — with out requiring any MCP integration.
    • AI brokers working in instruments like Cursor, Claude Code, and OpenCode might be arrange with two instructions and a single pure language instruction, after which the agent learns the complete command interface by itself from the bundled SKILL.md documentation.
    • The CLI is designed for programmatic and agent use, with devoted flags for non-interactive execution, a clear stdout/stderr separation for secure piping, structured exit codes for error dealing with, and a schema export function that lets agent frameworks register mmx instructions as JSON instrument definitions.
    • For AI devs already constructing agent-based programs, it lowers the mixing barrier considerably by consolidating picture, video, speech, music, imaginative and prescient, and search era right into a single, well-documented CLI that brokers can be taught and function on their very own.

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    Shobha is an information analyst with a confirmed observe report of creating revolutionary machine-learning options that drive enterprise worth.



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    Naveed Ahmad

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