The Kaltura MCP Server provides secure, read-only access to Kaltura media content and analytics, enabling AI-assisted discovery and analysis.
- Media Discovery & Management: Search, filter, and sort media entries by criteria like creation date, views, plays, and relevance. Retrieve detailed information, download URLs, thumbnails, captions, and attachments.
- Category Management: List and search content categories with optional limits and search text.
- Comprehensive Analytics: Access data on content performance, user engagement, geographic distribution, and Quality of Experience (QoE) metrics with support for multiple report types and filtering options.
- Secure Access: Ensures read-only operations with input validation, encrypted credential storage, and JWT token management for remote server access.
- Flexible Deployment: Supports both local development (Stdio mode) and remote deployment (HTTP/SSE mode) with TLS encryption in production environments.
Provides Docker support for running the Kaltura MCP server through pre-built multi-architecture Docker images or building locally with Docker Compose.
Hosts the Kaltura MCP server repository and provides the container registry for the pre-built Docker images.
Officially supports running the Kaltura MCP server on Linux operating systems.
Officially supports running the Kaltura MCP server on macOS operating systems.
Requires Python 3.10 or higher for installation and running of the Kaltura MCP server.
Supports YAML format for the server's configuration system, allowing users to provide API credentials and other settings.
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):
Option 2: Building Locally with Docker Compose
Alternatively, you can build the image locally:
Manual Installation
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:
- You can also use environment variables for configuration:
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 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 user
Available Resources
The Kaltura MCP Server provides the following resources:
media://{entry_id}
: Media entry metadatacategory://{category_id}
: Category metadatauser://{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.
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.
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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