Kaltura MCP Server

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 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

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.

Install Server

HTTP connection URL

security – no known vulnerabilities

license - permissive license

quality - confirmed to work

How are these scores calculated?

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

Tools

An implementation of the Model Context Protocol that provides AI models with standardized access to Kaltura's media management capabilities including uploading, retrieving metadata, searching, and managing categories and permissions.

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