Luma's new MCP connector runs its image and video workflows inside Claude and ChatGPT, and Claude Motion animations open straight in Luma. 5 hours ago Image: Luma AI, Luma and Claude launch graphic, via Luma Luma, the AI video and image company, has released an MCP connector so Claude and ChatGPT can run Luma's creative workflows from inside a chat. In its announcement, Luma says you can ask your assistant which of last week's ads performed best, then have Luma restyle the winning ad into new scenes, camera angles and lighting in the same conversation, with finished images and video returned in the chat. What the connector does. Luma lists these workflows on its MCP page: product shots, new camera angles from one photo, art style match, background swap, face swap, ad variants in every size and language, multi-angle shot coverage and a relight studio. The announcement adds the Luma Agent, which it describes as a creative partner that can orchestrate whole projects from one prompt, and short promo clips to take a finished look into motion. It is aimed at ad teams: Luma cites AppLovin data, reported by Marketing Dive, that advertisers refreshing creative nearly weekly over last year's Black Friday and Cyber Monday saw a 23% higher median 7-day return on ad spend. The pitch is one approved asset in, a full set of variants out. Luma says the connector draws on your own Luma credits and you connect your account once. For team workspaces, an owner or admin adds Luma first, then each person signs in. Setup in Claude. The MCP page walks through it: click Add Luma to Claude, Claude opens its connector window with Luma's name and URL filled in, click Add, then connect and sign in with your Luma account. There is also a manual route and a ChatGPT version. Luma shows screens from Claude on the web and says desktop looks the same. The Claude Motion link. The earlier partnership is the more interesting one for editors. In October Luma announced that Claude Motion animations can open directly in Luma. Claude Motion launched in beta for Team and Enterprise plans and does not use a video model: it writes code that animates your text, charts, shapes and images, and exports MP4. Luma's release says that through the connector the animation arrives in Luma as a video, where you can restyle the look while the motion holds, reframe to 9:16, 1:1, 4:3 or 21:9, or ask the agent for extra versions. That is a real workflow: build a clean, editable explainer in Claude, then let Luma's Ray and Uni models restyle and resize it. The code-built original means timing and numbers stay exact, which generated video cannot promise. What to question. Almost all of the examples are product and ad work, not film. Luma has not published pricing for how many credits a workflow burns, and generated restyles can drift from the original, so check numbers and logos on every variant. Face swap on client material needs consent and a clear license. And everything here is Luma describing its own product. For editors, the practical use is turnaround: one master cut, delivered in several aspect ratios and looks without opening a new tool. Then bring them into the timeline, grade them to match, and unify the look with real grain: Grainzilla's free film grain download is a quick test on one variant. Assistants that can call a video tool are convenient. The edit still belongs to whoever decides which variant ships. Cart. * Your cart is empty.

How to create brand campaign videos with Luma Dream Machine on Pollo AI. Creating brand campaign videos isn't always easy for small businesses, ecommerce sellers, or marketing teams. Every campaign often needs multiple versions for different products, promotions, and social platforms, but producing fresh videos regularly can quickly become expensive and time-consuming. Luma Dream Machine on Pollo AI offers a more efficient workflow. By combining Luma AI's video generation model with Pollo AI's all-in-one creative platform, users can create promotional videos from text prompts or existing product images without constantly switching between different tools. This guide explains how to get better results, avoid common mistakes, and use the model more effectively for marketing content. What is Luma Dream Machine on Pollo AI? Luma Dream Machine is an AI video generation model developed by Luma AI. It creates short videos from either text prompts or still images and is known for producing realistic motion, cinematic camera movement, and visually consistent scenes. Luma Dream Machine on Pollo AI brings these capabilities into Pollo AI's all-in-one creative platform. Instead of using the model as a standalone tool, users can generate videos alongside other leading AI image and video models, reuse prompts, and switch between workflows without leaving the platform. For businesses, it offers a more practical production experience. Besides generating videos, users can easily combine it with Pollo AI's marketing-focused tools to create product videos, AI avatars, and other promotional assets, making it easier to develop complete campaign content within a single workspace. Why use Luma Dream Machine on Pollo AI for brand campaign videos? Brand campaigns rarely end with a single video. Marketing teams often need different versions for various audiences, products, or platforms, making speed and flexibility just as important as visual quality. This is where Luma Dream Machine on Pollo AI stands out. Teams can quickly test multiple creative directions by adjusting prompts, camera movement, or environments instead of waiting for new edits each time. Existing product photos can also be animated into promotional videos, making it easier for ecommerce businesses to reuse the assets they already have. The experience is further improved by Pollo AI itself. Since video generation, image creation, and other marketing tools - including its AI marketing video generator - are available in the same workspace, users can complete more of the production process without switching platforms. Step 1. Define the campaign before writing prompts. Many beginners immediately start writing prompts, but planning the campaign first usually produces better results. Before opening Luma Dream Machine on Pollo AI, decide what the video should achieve. Is it introducing a new product, promoting a seasonal sale, or increasing brand awareness? The answer will influence the video's style, pacing, and overall message. It is also helpful to determine where the video will be published. A short vertical video for TikTok or Instagram Reels may require a different approach from a landscape video designed for YouTube or a homepage banner. The clearer the campaign objective, the easier it becomes to write effective prompts later. Step 2. Choose between text-to-video and image-to-video. After selecting Luma Dream Machine on Pollo AI, choose the generation method that best matches the project. Text-to-video is suitable when developing new campaign concepts or exploring creative ideas from scratch. Image-to-video is often a better choice when the campaign already has product photography or brand visuals. Using existing assets helps maintain visual consistency while reducing the amount of prompt engineering required. If brand identity is important, starting from high-quality product images generally produces more reliable results than relying entirely on text descriptions. Step 3. Write specific prompts instead of long descriptions. Prompt quality has a major impact on the final video. Rather than filling the prompt with dozens of descriptive adjectives, focus on a few essential elements: * The main subject * The environment * Lighting * Camera movement * Overall mood * Visual style For example, instead of writing: "Create a beautiful advertisement for my product." A more useful prompt would be: "Premium skincare bottle on a marble countertop, warm morning sunlight, slow cinematic dolly shot, luxury commercial style, soft reflections, minimalist background." Keeping one clear subject in each prompt usually produces more stable outputs. Trying to describe multiple products, several people, and numerous actions in a single prompt may lead to inconsistent scenes or unexpected object changes. Step 4. Use product images carefully. When using image-to-video, image quality matters. A clear, high-resolution product photo with consistent lighting generally gives the model better visual information than a heavily compressed image. Users should also review generated videos carefully before publishing. AI models may occasionally alter small product details, packaging, logos, or colors. While these changes are often minor, they can be important for branded marketing materials. If visual accuracy is essential, generating several versions and selecting the most consistent result is usually worthwhile. Step 5. Generate multiple versions instead of accepting the first result. One advantage of AI video generation is the ability to experiment quickly. Rather than downloading the first output, generate several variations by adjusting camera movement, lighting, environments, or prompt wording. Often, small prompt changes can noticeably improve motion quality or visual storytelling. Comparing three to five versions usually provides a better chance of finding a video that matches the campaign's creative direction. This iterative workflow is common among marketing teams because it allows creative decisions to be based on comparison rather than a single AI output. Step 6. Complete branding during editing. Although Luma Dream Machine on Pollo AI can generate visually appealing scenes, the generated video is often only one part of a finished campaign. Elements such as brand logos, pricing, subtitles, music, and calls to action are usually more reliable when added in a video editor after generation. AI-generated text can still contain inaccuracies, so relying on post-production helps maintain brand consistency. This final editing stage also makes it easier to adapt the same video for multiple platforms without regenerating the entire clip. Common mistakes and practical tips. Several simple practices can significantly improve results. Avoid writing extremely long prompts that describe too many subjects or actions. A focused prompt usually generates cleaner motion and more coherent scenes. If the campaign depends on accurate branding, always verify product details, logos, and packaging before publishing, especially when using image-to-video generation. Generate multiple versions rather than expecting the first result to be perfect. AI video creation is typically an iterative process where small prompt adjustments lead to noticeable improvements. Finally, keep realistic expectations. Luma Dream Machine on Pollo AI performs well for short promotional videos and concept development, but it is not intended to replace professional editing software for long-form productions or frame-by-frame creative control. For campaigns requiring highly precise branding or complex visual effects, additional editing may still be necessary. Conclusion. Luma Dream Machine on Pollo AI offers businesses a practical way to create brand campaign videos from text prompts or existing product images. By combining Luma Dream Machine's realistic video generation with Pollo AI's marketing-oriented creative platform, users can experiment with campaign ideas, produce multiple promotional variations, and streamline content production within a single workspace. For small businesses, ecommerce sellers, and marketing teams that regularly create promotional content, understanding prompt design, reviewing AI-generated details carefully, and treating AI generation as part of a broader production workflow will generally produce the most effective results.