The Kaltura MCP Server is an implementation of the Model Context Protocol (MCP) that provides AI models with access to Kaltura's media management capabilities. This server enables AI models to:
By implementing the Model Context Protocol, this server allows AI models to interact with Kaltura's API in a standardized way, making it easier to integrate Kaltura's capabilities into AI workflows.
pyproject.toml
for a complete listThe kaltura-mcp-public
repository contains the complete, self-contained Kaltura MCP server implementation, including:
The easiest way to get started is with our pre-built multi-architecture Docker image (supports both x86_64/amd64 and ARM64/Apple Silicon):
# Pull the latest image
docker pull ghcr.io/zoharbabin/kaltura-mcp:latest
# Create a config file
cp config.yaml.example config.yaml
# Edit config.yaml with your Kaltura API credentials
# Run the container
docker run -p 8000:8000 -v $(pwd)/config.yaml:/app/config.yaml ghcr.io/zoharbabin/kaltura-mcp:latest
Alternatively, you can build the image locally:
# Clone the repository
git clone https://github.com/zoharbabin/kaltura-mcp.git
cd kaltura-mcp
# Build and run with Docker Compose
docker-compose up
# Clone the repository
git clone https://github.com/zoharbabin/kaltura-mcp.git
cd kaltura-mcp
# Create a virtual environment (Python 3.10 or higher required)
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install dependencies
pip install -e .
# Configure the server
cp config.yaml.example config.yaml
# Edit config.yaml with your Kaltura API credentials
# Run the server
python -m kaltura_mcp.server
The Kaltura MCP Server supports a unified configuration system that works with both YAML and JSON formats. To get started:
config.yaml.example
to config.yaml
and edit it with your Kaltura API credentials:kaltura:
partner_id: YOUR_PARTNER_ID
admin_secret: YOUR_ADMIN_SECRET
user_id: YOUR_USER_ID
service_url: https://www.kaltura.com/api_v3
export KALTURA_PARTNER_ID=YOUR_PARTNER_ID
export KALTURA_ADMIN_SECRET=YOUR_ADMIN_SECRET
export KALTURA_USER_ID=YOUR_USER_ID
For more detailed configuration options, see the Configuration Guide.
To use the Kaltura MCP Server with Claude, see the Using with Claude guide.
To use the Kaltura MCP Server with the MCP CLI, see the Using with MCP CLI guide.
To use the Kaltura MCP Server programmatically, see the examples directory.
The Kaltura MCP Server provides the following tools:
media_upload
: Upload media files to Kalturamedia_get
: Retrieve media metadatamedia_update
: Update media metadatamedia_delete
: Delete mediacategory_list
: List categoriescategory_get
: Retrieve category metadatacategory_add
: Add a new categorycategory_update
: Update category metadatacategory_delete
: Delete a categoryuser_list
: List usersuser_get
: Retrieve user metadatauser_add
: Add a new useruser_update
: Update user metadatauser_delete
: Delete a userThe Kaltura MCP Server provides the following resources:
media://{entry_id}
: Media entry metadatacategory://{category_id}
: Category metadatauser://{user_id}
: User metadataSee CONTRIBUTING.md for details on how to contribute to this project.
This project is licensed under the AGPLv3 License - see the LICENSE file for details.
A Model Context Protocol (MCP) server that enables AI models to interact with Kaltura's media management platform. Allows AI assistants to upload, retrieve, search, and manage media content through a standardized protocol interface.
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