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Kaltura-MCP
Un servidor de Protocolo de contexto modelo (MCP) que permite a los modelos AI interactuar con la plataforma de gestión de medios de Kaltura. Permite a los asistentes de IA cargar, recuperar, buscar y administrar el contenido de los medios a través de una interfaz de protocolo estandarizada.
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Kaltura Model Context Protocol (MCP) Server
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.
Overview
This server enables AI models to:
- Upload media to Kaltura
- Retrieve media metadata
- Search for media
- Manage categories
- Manage users and permissions
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.
Requirements
- Python: 3.10 or higher (3.10, 3.11, 3.12 are officially supported)
- Operating Systems: Linux, macOS, Windows
-
Dependencies: See
pyproject.toml
for a complete list
Repository Structure
The kaltura-mcp-public
repository contains the complete, self-contained Kaltura MCP server implementation, including:
- All necessary code
- Comprehensive documentation
- Docker support
- Setup script
- Example clients
- Test scripts
Installation
Using Docker
Option 1: Using Pre-built Docker Image
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
Option 2: Building Locally with Docker Compose
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
Manual Installation
# 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
Configuration
The Kaltura MCP Server supports a unified configuration system that works with both YAML and JSON formats. To get started:
- Copy
config.yaml.example
toconfig.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
- You can also use environment variables for configuration:
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.
Usage
With Claude
To use the Kaltura MCP Server with Claude, see the Using with Claude guide.
With the MCP CLI
To use the Kaltura MCP Server with the MCP CLI, see the Using with MCP CLI guide.
Programmatically
To use the Kaltura MCP Server programmatically, see the examples directory.
Available Tools
The Kaltura MCP Server provides the following tools:
-
media_upload
: Upload media files to Kaltura -
media_get
: Retrieve media metadata -
media_update
: Update media metadata -
media_delete
: Delete media -
category_list
: List categories -
category_get
: Retrieve category metadata -
category_add
: Add a new category -
category_update
: Update category metadata -
category_delete
: Delete a category -
user_list
: List users -
user_get
: Retrieve user metadata -
user_add
: Add a new user -
user_update
: Update user metadata -
user_delete
: Delete a user
Available Resources
The Kaltura MCP Server provides the following resources:
-
media://{entry_id}
: Media entry metadata -
category://{category_id}
: Category metadata -
user://{user_id}
: User metadata
Contributing
See CONTRIBUTING.md for details on how to contribute to this project.
License
This project is licensed under the AGPLv3 License - see the LICENSE file for details.
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Reviews

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