by burningion
AI-powered video editor that integrates Video Jungle for natural-language YouTube video search, automated clip generatio
Connects to Video Jungle API for AI-powered video editing, allowing you to upload videos, search content with natural language, and automatically generate video edits.
Video Editor is a community-built MCP server published by burningion that provides AI assistants with tools and capabilities via the Model Context Protocol. AI-powered video editor that integrates Video Jungle for natural-language YouTube video search, automated clip generatio It is categorized under other, productivity.
You can install Video Editor in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
Video Editor is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
I recommend Video Editor for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Strong directory entry: Video Editor surfaces stars and publisher context so we could sanity-check maintenance before adopting.
According to our notes, Video Editor benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Video Editor is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Strong directory entry: Video Editor surfaces stars and publisher context so we could sanity-check maintenance before adopting.
We wired Video Editor into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Video Editor has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
We evaluated Video Editor against two servers with overlapping tools; this profile had the clearer scope statement.
Video Editor is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
We evaluated Video Editor against two servers with overlapping tools; this profile had the clearer scope statement.
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See a demo here: https://www.youtube.com/watch?v=KG6TMLD8GmA
Upload, edit, search, and generate videos from everyone's favorite LLM and Video Jungle.
You'll need to sign up for an account at Video Jungle in order to use this tool, and add your API key.
The server implements an interface to upload, generate, and edit videos with:
Coming soon.
The server implements a few tools:
In order to use the tools, you'll need to sign up for Video Jungle and add your API key.
add-video
Here's an example prompt to invoke the add-video tool:
can you download the video at https://www.youtube.com/shorts/RumgYaH5XYw and name it fly traps?
This will download a video from a URL, add it to your library, and analyze it for retrieval later. Analysis is multi-modal, so both audio and visual components can be queried against.
search-videos
Once you've got a video downloaded and analyzed, you can then do queries on it using the search-videos tool:
can you search my videos for fly traps?
Search results contain relevant metadata for generating a video edit according to details discovered in the initial analysis.
search-local-videos
You must set the environment variable LOAD_PHOTOS_DB=1 in order to use this tool, as it will make Claude prompt to access your files on your local machine.
Once that's done, you can search through your Photos app for videos that exist on your phone, using Apple's tags.
In my case, when I search for "Skateboard", I get 1903 video files.
can you search my local video files for Skateboard?
generate-edit-from-videos
Finally, you can use these search results to generate an edit:
can you create an edit of all the times the video says "fly trap"?
(Currently), the video edits tool relies on the context within the current chat.
generate-edit-from-single-video
Finally, you can cut down an edit from a single, existing video:
can you create an edit of all the times this video says the word "fly trap"?
You must login to Video Jungle settings, and get your API key. Then, use this to start Video Jungle MCP:
$ uv run video-editor-mcp YOURAPIKEY
To allow this MCP server to search your Photos app on MacOS:
$ LOAD_PHOTOS_DB=1 uv run video-editor-mcp YOURAPIKEY
To install Video Editor for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install video-editor-mcp --client claude
You'll need to adjust your claude_desktop_config.json manually:
On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
"mcpServers": {
"video-editor-mcp": {
"command": "uvx",
"args": [
"video-editor-mcp",
"YOURAPIKEY"
]
}
}
"mcpServers": {
"video-editor-mcp": {
"command": "uv",
"args": [
"--directory",
"/Users/YOURDIRECTORY/video-editor-mcp",
"run",
"video-editor-mcp",
"YOURAPIKEY"
]
}
}
With local Photos app access enabled (search your Photos app):
"video-jungle-mcp": {
"command": "uv",
"args": [
"--directory",
"/Users/<PATH_TO>/video-jungle-mcp",
"run",
"video-editor-mcp",
"<YOURAPIKEY>"
],
"env": {
"LOAD_PHOTOS_DB": "1"
}
},
Be sure to replace the directories with the directories you've placed the repository in on your computer.
To prepare the package for distribution:
uv sync
uv build
This will create source and wheel distributions in the dist/ directory.
uv publish
Note: You'll need to set PyPI credentials via environment variables or command flags:
--token or UV_PUBLISH_TOKEN--username/UV_PUBLISH_USERNAME and --password/UV_PUBLISH_PASSWORDmcp-name: io.github.burningion/video-editing-mcp
Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.
You can launch the MCP Inspector via npm with this command:
(Be sure to replace YOURDIRECTORY and YOURAPIKEY with the directory this repo is in, and your Video Jungle API key, found in the settings page.)
npx @modelcontextprotocol/inspector uv run --directory /Users/YOURDIRECTORY/video-editor-mcp video-editor-mcp YOURAPIKEY
Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.
Additionally, I've added logging to app.log in the project directory. You can add logging to diagnose API calls via a:
logging.info("this is a test log")
A reasonable way to follow along as you're workin on the project is to open a terminal session and do a:
$ tail -n 90 -f app.log
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.