Gumlet MCP. Manage your media assets from chat, not dashboards.
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Gumlet MCP manages your entire media workflow, letting you handle video uploads, image optimization, and CDN delivery straight through conversation.
It gives you control over complex assets—from listing folders to checking viewing stats—without opening a dashboard or writing code.
What your AI agents can do
Create video upload
Initiates the process of uploading and processing a brand-new video asset.
Create collection
Adds a new folder to your media library organization structure.
Delete video
Removes an existing video asset from your account.
Create new folders or collections for videos and images to keep your assets structured.
Upload new video files, track their transcoding status, and monitor the overall health of your media library.
Retrieve real-time analytics on viewing stats, bandwidth consumption, and asset performance for specific videos.
Programmatically update video thumbnails by specifying exact frames or time offsets.
List team members and manage the sources used for image optimization to maintain content integrity.
Ask AI about this MCP
Supported MCP Clients
OAuth 2.0 Compatible Gemini Waiting for input…
Gumlet: 12 Media Management Tools
Use these tools to control every part of your video and image pipeline—from uploading new content to checking detailed usage metrics.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Gumlet on Vinkius019dd0ffcreate video upload
Initiates the process of uploading and processing a brand-new video asset.
019dd0ffcreate collection
Adds a new folder to your media library organization structure.
019dd0ffdelete video
Removes an existing video asset from your account.
019dd0ffget video details
Checks the current status of a video asset, including its transcoding progress.
019dd0ffget account info
Retrieves basic details about your Gumlet profile and account settings.
019dd0ffget video analytics
Fetches detailed statistics, such as unique views and bandwidth usage, for a specific video.
019dd0fflist videos
Gets a comprehensive listing of all current video assets in the account.
019dd0fflist video collections
Retrieves a list of all existing video folders in your library.
019dd0fflist image sources
Shows all available sources used for optimizing your image delivery.
019dd0fflist org users
Lists the team members and users who have access to the account.
019dd0fflist webhooks
Retrieves information about any active webhooks configured for your account.
019dd0ffupdate video thumbnail
Sets a new thumbnail image by specifying the exact time or frame offset within a video.
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Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 12 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Managing your video assets used to be a dashboard nightmare.
Remember having to check 5 different tabs—one for uploads, one for folders, and another for stats? You'd copy the asset ID from one place and paste it into a separate status checker. If you needed analytics, you had to wait for the video to finish processing before you could even start pulling data.
Now, your agent handles all of that. You tell it what needs doing—whether it’s listing assets or checking bandwidth usage—and it executes the complex sequence behind the scenes. The result is a single answer: 'It's ready.' No more dashboard jumping.
The Gumlet MCP gives you full control over your media lifecycle.
You no longer need to manually list folders via one screen, then go to another screen to upload the file. You can ask the agent to create a new folder (`create_collection`) and immediately process an upload into it (`create_video_upload`).
The difference is control. Instead of being limited by web UI flows, you manage every single asset, from listing users with `list_org_users` to updating specific frames using `update_video_thumbnail`, all through natural conversation.
What you can do with this MCP connector
Stop navigating clunky web dashboards just to check if an upload finished or grab some analytics. This MCP lets your AI agent treat Gumlet like a dedicated media operations team. You manage video life cycles, build structured collections, and handle image source updates using natural language conversation.
It's about getting data when you need it. Need to know how many people watched last week? Just ask. Want to move an asset into a new folder or update that crucial thumbnail frame? Tell the agent. The whole process—from listing available users to deleting old videos and checking bandwidth usage—happens instantly through your AI client.
By connecting Gumlet via Vinkius, you turn complex media infrastructure management into simple chat commands.
019dd100-0ecf-7344-a4df-e3f55b6e7e05 
How Gumlet MCP Works
- 1 Subscribe to this MCP and retrieve your API Key from your Gumlet account dashboard.
- 2 Connect that key in your preferred AI client (like Cursor or Claude).
- 3 Ask your agent what you need done—for example, 'Check the stats for the Annual Report video'—and it executes the task directly against your media assets.
The bottom line is, instead of logging into a website and clicking through menus, you just talk to your AI client about your media needs.
Who Is Gumlet MCP For?
This MCP solves the problem for anyone whose job involves managing high volumes of visual content. It’s for the Content Manager who is tired of clicking through multiple asset tabs, and the Developer who needs to integrate media workflows without writing complex boilerplate API calls.
Retrieving viewing analytics on specific campaigns or updating video thumbnails across different client collections.
Maintaining a structured media library by creating new folders and managing team access to image sources.
Automating the ingestion of new assets, monitoring transcoding status, and listing all available video resources programmatically.
What Changes When You Connect
- Stop manually checking status. You can use
get_video_detailsto check a video's transcoding progress and know exactly when it's ready for public use. - Keep your content organized instantly by using
create_collectionor listing all folders withlist_video_collections, letting you structure huge media libraries without clicking through dozens of menus. - Never guess the stats again. Run
get_video_analyticsto pull viewing metrics and bandwidth usage for any video, giving you instant performance insights. - Fine-tune your visual marketing assets by calling
update_video_thumbnail, allowing you to select a specific time offset or frame for perfect visuals. - Manage team access easily. You can list all organizational users with
list_org_usersand check image source availability vialist_image_sourcesin one conversation.
Real-World Use Cases
Need to audit a campaign's reach?
A marketer needs to know how many unique views the 'Q3 Product Launch' video got last month and which regions are driving traffic. They ask their agent, and it calls get_video_analytics immediately, returning the data they need.
Need to move a finished asset?
A content manager finishes an initial draft video and needs to place it into the 'Client Approved' folder. The agent uses create_collection first (if needed) and then guides the upload, keeping the library perfectly structured.
Need to update branding visuals?
A developer is told the video thumbnail needs to show a specific product feature at 15 seconds. Instead of manually editing frames, they use update_video_thumbnail and provide the exact time code.
Need to clean up old data?
An ops engineer wants to clear out all the raw video files from 2018 that are no longer needed. They use list_videos to confirm the assets and then instruct the agent to run delete_video on the specific IDs.
The Tradeoffs
Listing all videos manually
The user tries to check if a video exists by opening the web dashboard and clicking 'Search,' getting lost in filters.
→
Instead, just ask your agent to run list_videos or use get_video_details with a known asset ID. It's faster.
Assuming one endpoint for everything
Trying to check if the video uploaded correctly and also get its stats from the same button.
→
First, use get_video_details to confirm transcoding status. Once that's done, call get_video_analytics to pull the performance data.
Ignoring organization structure
Uploading a new video and leaving it in the main root directory, making it hard for others to find later.
→
Before uploading, use list_video_collections to see what folders exist. Then, ask your agent to create or target the right folder using create_collection.
When It Fits, When It Doesn't
Use this MCP if managing media assets is a core part of your job. Specifically, you need to connect asset status (transcoding progress), performance data (get_video_analytics), and structured organization across multiple types of files. Don't use it if all you need is simple file storage—a cloud bucket service works fine there. Also, don't use it just for basic messaging or email sending; that’s a communication MCP job. This is purely for media pipeline control.
Common Questions About Gumlet MCP
How do I check if a video finished processing with get_video_details? +
You provide the asset ID, and the agent reports its status. It will confirm when transcoding is complete, letting you know exactly when it's ready for public use.
Can I organize my videos into specific folders using create_collection? +
Yes. The create_collection tool lets you programmatically build out your media library structure before uploading content to keep things tidy.
What is the best way to get performance data for a video? Use get_video_analytics? +
Yes, that's right. get_video_analytics pulls specific metrics like unique views and bandwidth consumption, giving you actionable insights without leaving your chat window.
Do I need to run list_videos before uploading a new video? +
No. While you can use list_videos at any time to see what's there, the upload process starts with create_video_upload, which handles the asset ingestion.
How do I check which team members are set up in my organization using list_org_users? +
It lists all current users and their associated roles. This lets you manage access and know who can view or contribute to your media assets.
What specific data does list_image_sources provide regarding my optimized images? +
This tool retrieves details about the image sources configured for optimization. You'll get the necessary identifiers and settings required to ensure high-fidelity delivery across all your content.
If I need to remove an old video asset, how do I use delete_video? +
You send this command with the specific video ID. This permanently removes the video from Gumlet and cleans up the associated storage space for you.
What is the purpose of list_webhooks when setting up my media pipeline? +
This checks all active webhooks connected to your account. It lets you verify which external services are receiving updates when key events, like uploads or status changes, occur.
How do I start a video upload? +
Use the create_video_upload tool, which will create the asset in your specified collection and provide a temporary upload_url for your file.
Can I update the thumbnail for a video already uploaded? +
Yes! The update_video_thumbnail tool allows you to specify a time offset in seconds. Gumlet will extract that specific frame and set it as the new thumbnail.
Does it support viewing stats and bandwidth usage? +
The get_video_analytics tool provides detailed viewing metrics and bandwidth consumption data for any video ID in your account.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.