
video-editing-mcp
MCP server for uploading, editing, searching, and generating videos via Video Jungle and LLMs.
Key Features
Use Cases
README
Video Editor MCP server
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.
Components
Resources
The server implements an interface to upload, generate, and edit videos with:
- Custom vj:// URI scheme for accessing individual videos and projects
- Each project resource has a name, description
- Search results are returned with metadata about what is in the video, and when, allowing for edit generation directly
Prompts
Coming soon.
Tools
The server implements a few tools:
- add-video
- Add a Video File for analysis from a URL. Returns an vj:// URI to reference the Video file
- create-videojungle-project
- Creates a Video Jungle project to contain generative scripts, analyzed videos, and images for video edit generation
- edit-locally
- Creates an OpenTimelineIO project and downloads it to your machine to open in a Davinci Resolve Studio instance (Resolve Studio must already be running before calling this tool.)
- generate-edit-from-videos
- Generates a rendered video edit from a set of video files
- generate-edit-from-single-video
- Generate an edit from a single input video file
- get-project-assets
- Get assets within a project for video edit generation.
- search-videos
- Returns video matches based upon embeddings and keywords
- update-video-edit
- Live update a video edit's information. If Video Jungle is open, edit will be updated in real time.
Using Tools in Practice
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"?
Configuration
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
Quickstart
Install
Installing via Smithery
To install Video Editor for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install video-editor-mcp --client claude
Claude Desktop
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.
Development
Building and Publishing
To prepare the package for distribution:
- Sync dependencies and update lockfile:
uv sync
- Build package distributions:
uv build
This will create source and wheel distributions in the dist/
directory.
- Publish to PyPI:
uv publish
Note: You'll need to set PyPI credentials via environment variables or command flags:
- Token:
--token
orUV_PUBLISH_TOKEN
- Or username/password:
--username
/UV_PUBLISH_USERNAME
and--password
/UV_PUBLISH_PASSWORD
Debugging
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
Star History
Repository Owner
User
Repository Details
Programming Languages
Join Our Newsletter
Stay updated with the latest AI tools, news, and offers by subscribing to our weekly newsletter.
Related MCPs
Discover similar Model Context Protocol servers

mcpmcp-server
Seamlessly discover, set up, and integrate MCP servers with AI clients.
mcpmcp-server enables users to discover, configure, and connect MCP servers with preferred clients, optimizing AI integration into daily workflows. It supports streamlined setup via JSON configuration, ensuring compatibility with various platforms such as Claude Desktop on macOS. The project simplifies the connection process between AI clients and remote Model Context Protocol servers. Users are directed to an associated homepage for further platform-specific guidance.
- ⭐ 17
- MCP
- glenngillen/mcpmcp-server

manim-mcp-server
MCP server for generating Manim animations on demand.
Manim MCP Server allows users to execute Manim Python scripts via a standardized protocol, generating animation videos that are returned as output. It integrates with systems like Claude to dynamically render animation content from user scripts and supports configurable deployment using environment variables. The server handles management of output files and cleanup of temporary resources, designed with portability and ease of integration in mind.
- ⭐ 454
- MCP
- abhiemj/manim-mcp-server

mcp
Universal remote MCP server connecting AI clients to productivity tools.
WayStation MCP acts as a remote Model Context Protocol (MCP) server, enabling seamless integration between AI clients like Claude or Cursor and a wide range of productivity applications, such as Notion, Monday, Airtable, Jira, and more. It supports multiple secure connection transports and offers both general and user-specific preauthenticated endpoints. The platform emphasizes ease of integration, OAuth2-based authentication, and broad app compatibility. Users can manage their integrations through a user dashboard, simplifying complex workflow automations for AI-powered productivity.
- ⭐ 27
- MCP
- waystation-ai/mcp

mcp-server-js
Enable secure, AI-driven process automation and code execution on YepCode via Model Context Protocol.
YepCode MCP Server acts as a Model Context Protocol (MCP) server that facilitates seamless communication between AI platforms and YepCode’s workflow automation infrastructure. It allows AI assistants and clients to execute code, manage environment variables, and interact with storage through standardized tools. The server can expose YepCode processes directly as MCP tools and supports both hosted and local installations via NPX or Docker. Enterprise-grade security and real-time interaction make it suitable for integrating advanced automation into AI-powered environments.
- ⭐ 31
- MCP
- yepcode/mcp-server-js

1mcp-app/agent
A unified server that aggregates and manages multiple Model Context Protocol servers.
1MCP Agent provides a single, unified interface that aggregates multiple Model Context Protocol (MCP) servers, enabling seamless integration and management of external tools for AI assistants. It acts as a proxy, managing server configuration, authentication, health monitoring, and dynamic server control with features like asynchronous loading, tag-based filtering, and advanced security options. Compatible with popular AI development environments, it simplifies setup by reducing redundant server instances and resource usage. Users can configure, monitor, and scale model tool integrations across various AI clients through easy CLI commands or Docker deployment.
- ⭐ 96
- MCP
- 1mcp-app/agent

blender-mcp
Seamless integration between Blender and Claude AI using the Model Context Protocol.
BlenderMCP enables direct interaction between Blender and Claude AI by leveraging the Model Context Protocol (MCP). It allows users to create, manipulate, and inspect 3D scenes in Blender through natural language commands sent to Claude, which communicates with Blender via a custom socket server and an addon. The solution features two-way communication, object and material manipulation, code execution within Blender, and easy integration with tools like Cursor, Visual Studio Code, and Claude for Desktop.
- ⭐ 13,092
- MCP
- ahujasid/blender-mcp
Didn't find tool you were looking for?