Shaka Packager MCP Server
This server integrates Shaka Packager with Claude AI applications through the Model Context Protocol (MCP) for advanced video processing, packaging, and analysis.
Core Capabilities:
Video Analysis - Extract detailed stream information, codecs, bitrates, resolution, and technical metadata from video files
Media Packaging - Convert videos for streaming in HLS and DASH formats with support for VOD and live streaming
Format Conversion - Convert between video formats (MP4, TS, etc.)
DRM Encryption - Apply content protection with Widevine, PlayReady, and FairPlay
Ad Insertion - Configure markers and prepare videos for advertisement insertion
Custom Command Execution - Run any Shaka Packager command with custom arguments
Documentation Access - Retrieve comprehensive documentation, command structure, and usage examples
Intelligent Path Handling - Automatically translates paths between Docker and host environments
Error Analysis - Provides meaningful error messages with resolution suggestions
Available Tools:
analyze_video- Analyze video files to extract stream informationrun_shaka_packager- Execute custom Shaka Packager commands with specified argumentsget_shaka_documentation- Retrieve comprehensive documentation and examplesget_shaka_options- Get available command options and version information
Integration: Works with Claude Desktop and other MCP-compatible clients, alongside the Filesystem MCP Server for local file access. Supports both local file paths and file:// URIs.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Shaka Packager MCP Serveranalyze the video at /videos/sample.mp4 and tell me its codec and resolution"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Shaka Packager MCP Server
⚠️ EXPERIMENTAL STATUS DISCLAIMER
This project is in early alpha stage and is highly experimental. It is not recommended for production use. It is also likely MESSY!
Current limitations:
You may run into inconsistent behavior
Advanced features (packaging, conversion, etc.) are still under active development
Path translation between Docker and host environments may require manual configuration
Expect frequent breaking changes and potential instability
Please report any issues you encounter to help improve the project.
An MCP (Model Context Protocol) server that integrates Shaka Packager with Claude AI applications for video transcoding, packaging, and analysis.
This server works with the Filesystem MCP Server to enable Claude Desktop to access and process video files on your computer, turning Claude into a powerful assistant for media processing tasks.
Features
Video Analysis: Analyze video files to extract detailed stream information, codecs, bitrates, and more
Media Packaging: Convert videos for streaming in HLS and DASH formats with support for VOD and live streaming
Advanced Options:
Apply DRM encryption (Widevine, PlayReady, FairPlay)
Configure ad insertion markers
Convert between formats (MP4, TS, etc.)
Intelligent Path Handling: Automatically translates paths between Docker and host environments
Robust Error Management: Provides meaningful error analysis with suggestions for resolution
Command Assistance: Helps correctly format Shaka Packager commands for optimal results
Interactive Documentation: Built-in help and examples to guide users through complex operations
Detailed Outputs: Comprehensive summaries and execution details for all operations
Related MCP server: encoding-devops
Prerequisites
Python 3.10 or higher
Shaka Packager installed and available in your PATH
Or build from source following these instructions
An MCP-compatible client (like Claude Desktop)
Installation
Using pip or uv (coming soon)
Install the package with pip:
pip install shaka-packager-mcpOr with uv:
uv pip install shaka-packager-mcpFrom source (recommended)
git clone https://github.com/coderjun/shaka-packager-mcp.git
cd shaka-packager-mcp
pip install -e .Or with uv:
git clone https://github.com/coderjun/shaka-packager-mcp.git
cd shaka-packager-mcp
uv pip install -e .Claude Desktop Integration
Since Claude Desktop doesn't directly support uploading video files, we'll use a two-server approach:
A simplified filesystem MCP server to access video files on your computer
The Shaka Packager MCP server to analyze and process those videos
Step 1: Set Up the MCP Filesystem Server
Use the official MCP filesystem server to allow Claude to access your video files:
Install the official filesystem server with Docker:
docker pull mcp/filesystemAlternatively, you can build it from source following the instructions in the Filesystem MCP Server repository
Step 2: Find the Configuration File
Locate your Claude Desktop configuration file:
macOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:
%APPDATA%\Claude\claude_desktop_config.json
If the file doesn't exist, create it.
Step 3: Add Both Servers to the Configuration
Add the following configuration, making sure to use absolute paths:
{
"mcpServers": {
"filesystem": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"--mount", "type=bind,src=/PATH/TO/VIDEOS/DIRECTORY,dst=/projects/video-drop",
"mcp/filesystem",
"/projects"
]
},
"shaka-packager": {
"command": "/ABSOLUTE/PATH/TO/uv",
"args": [
"run",
"--with",
"mcp[cli]",
"/ABSOLUTE/PATH/TO/shaka_packager_mcp.py"
],
"env": {
"VIDEO_PATH": "/PATH/TO/VIDEOS/DIRECTORY",
"SHAKA_PACKAGER_PATH": "/PATH/TO/PACKAGER"
}
}
}
}Replace:
/PATH/TO/VIDEOS/DIRECTORYwith the path to the directory containing your video files/ABSOLUTE/PATH/TO/uvwith the full path to your uv executable/ABSOLUTE/PATH/TO/shaka_packager_mcp.pywith the full path to the script file/PATH/TO/PACKAGERwith the full path to your Shaka Packager executable
For example:
{
"mcpServers": {
"filesystem": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"--mount", "type=bind,src=/Users/username/Videos,dst=/projects/video-drop",
"mcp/filesystem",
"/projects"
]
},
"shaka-packager": {
"command": "/Users/username/.local/bin/uv",
"args": [
"run",
"--with",
"mcp[cli]",
"/Users/username/Development/shaka-packager-mcp/shaka_packager_mcp.py"
],
"env": {
"VIDEO_PATH": "/Users/username/Videos",
"SHAKA_PACKAGER_PATH": "/Users/username/.shaka/packager"
}
}
}
}Step 4: Restart Claude Desktop
After editing the configuration file, restart Claude Desktop to apply the changes.
How to Use the Two-Server Approach
First, browse your video files using the simplified filesystem server:
Ask Claude to "List the files in my video directory"
Navigate to the video file you want to analyze or process
Once you've found your video file, use its path with the Shaka Packager tools:
For analysis: "Please analyze this video: /Users/username/Videos/example.mp4"
For processing: "Please package this video for HLS: /Users/username/Videos/example.mp4"
Troubleshooting
If you encounter any issues:
Make sure both servers are properly configured with absolute paths
Verify that Shaka Packager is installed and accessible
Ensure the directory specified for the filesystem server exists and contains videos
Check Claude Desktop logs for errors at:
macOS:
~/Library/Logs/Claude/mcp*.logWindows:
%APPDATA%\Claude\logs\mcp*.log
Usage
Once both the Filesystem MCP server and the Shaka Packager MCP server are running in Claude Desktop:
Access your video files:
Please show me the files in my Videos directoryNavigate to your video file:
Please show me the files in the Movies subdirectoryCopy the file:// URI path of the video you want to process
Use the Shaka Packager tools with the file path:
Please analyze this video: file:///Users/username/Videos/my_video.mp4or
Please package this video for HLS and DASH streaming: file:///Users/username/Videos/my_video.mp4The server will execute the appropriate Shaka Packager command and provide a detailed summary of the results
You can also use direct file paths if you know the exact location of your video files:
Please analyze this video: /Users/username/Videos/my_video.mp4Tools
The server provides these tools:
analyze_video: Examines a video file and provides detailed stream information with intelligent error handling
run_shaka_packager: Executes any Shaka Packager command with custom arguments and proper path handling
get_shaka_options: Retrieves available command options and version information
get_shaka_documentation: Provides comprehensive documentation and examples for using Shaka Packager
Prompts
The server includes these prompt templates:
MP4 to TS conversion
VOD packaging in HLS and DASH
Live streaming packaging
Content encryption
Ad insertion preparation
Video analysis
Command format reminder
Error interpretation guidance
Configuration
The server can be configured using environment variables:
SHAKA_PACKAGER_PATH: Path to the Shaka Packager executable (highly recommended for Claude Desktop)VIDEO_PATH: Path to your local video directory (used for translating paths between Docker and host)DOCKER_PATH: Docker container mount path (default: "/projects/video-drop")TEMP_DIR: Custom temporary directory for file uploadsLOG_LEVEL: Logging level (DEBUG, INFO, WARNING, ERROR, CRITICAL)COMMAND_TIMEOUT: Timeout in seconds for Shaka Packager commands (default: 300)
You can set these in:
Your Claude Desktop configuration file (preferred for
SHAKA_PACKAGER_PATHandVIDEO_PATH)Your environment variables
A
.envfile in the same directory as the script
Example .env file:
SHAKA_PACKAGER_PATH=/usr/local/bin/packager
VIDEO_PATH=/Users/yourusername/Videos
LOG_LEVEL=DEBUGDevelopment
Setting up a development environment
# Clone the repository
git clone https://github.com/coderjun/shaka-packager-mcp.git
cd shaka-packager-mcp
# Install development dependencies with pip
pip install -e ".[dev]"
# Or with uv
uv pip install -e ".[dev]"Running tests
pytestCode formatting
black .
isort .Understanding the Code Structure
The main components of the Shaka Packager MCP server are:
shaka_packager_mcp.py: Main server implementation with MCP tools and promptstests/: Test suite for verifying functionality
This server is designed to work with the official MCP filesystem server for accessing video files.
Key Features in the Implementation
Robust path handling: Automatically translates paths between Docker and host environments
Smart error handling: Provides meaningful error messages and suggestions
Command syntax assistance: Helps correctly format Shaka Packager commands
Documentation integration: Provides comprehensive documentation and examples
License
This project is licensed under the MIT License - see the LICENSE file for details.
Getting Help
Feel free to use an AI code copilot, the author does.
If you encounter any issues or have questions:
Check the troubleshooting section in this README
Review the Shaka Packager documentation
Use the
get_shaka_documentationtool for interactive help within ClaudeOpen an issue on GitHub
Acknowledgements
Shaka Packager for the powerful video processing capabilities
Model Context Protocol (MCP) for the communication framework
Claude for the AI assistant capabilities
Anthropic for developing Claude and the MCP standard
Available Tools
4 toolsanalyze_videoB
Analyze a video file using Shaka Packager.
Args:
file_path: Path to the video file. Can be a local file path or a file:// URI from the filesystem MCP.
| Name | Required | Description | Default |
|---|---|---|---|
| file_path | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool analyzes a video file but doesn't describe what the analysis entails (e.g., format detection, metadata extraction, error checking), how long it might take, whether it modifies the file, or any rate limits. The mention of 'file:// URI from the filesystem MCP' hints at integration but lacks depth. For a tool with no annotations, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, starting with the core purpose. The two sentences are efficient, with the second providing parameter details. There's no wasted text, though it could be slightly more structured (e.g., bullet points). It earns its place but isn't perfectly polished.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which handles return values), no annotations, and low parameter complexity (1 param with 0% schema coverage), the description is moderately complete. It covers the purpose and parameter semantics adequately but lacks behavioral details and usage guidelines. For a simple analysis tool, it's acceptable but has clear gaps in guiding the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, so the description must compensate. It adds meaningful context for the single parameter 'file_path' by explaining it can be a local file path or a file:// URI from the filesystem MCP, which clarifies usage beyond the schema's basic string type. However, it doesn't detail constraints like supported file formats or path examples, keeping it from a perfect score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Analyze a video file') and the resource ('video file'), and mentions the specific tool used ('Shaka Packager'). However, it doesn't explicitly differentiate this tool from its siblings (get_shaka_documentation, get_shaka_options, run_shaka_packager), which would require a 5. The purpose is specific but lacks sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus its siblings. It mentions the tool's capability but doesn't specify contexts, prerequisites, or alternatives. For example, it doesn't explain when to choose analyze_video over run_shaka_packager or how it relates to get_shaka_options. This leaves the agent with minimal usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_shaka_documentationB
Get comprehensive Shaka Packager documentation, including command structure and examples.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves documentation but doesn't specify format (e.g., HTML, text), access requirements, rate limits, or error handling. This leaves gaps for a tool with no annotation coverage, though it correctly implies a read-only operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('Get comprehensive Shaka Packager documentation') and adds useful details without waste. Every word earns its place, making it appropriately sized for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, output schema provided), the description is mostly complete. It clearly states what the tool does, though it lacks behavioral details like output format or usage context. The presence of an output schema reduces the need to explain return values, but more guidance on when to use it would enhance completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description adds no parameter information, which is acceptable here as there are no parameters to explain, aligning with the baseline for zero parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('Shaka Packager documentation'), including scope details like 'command structure and examples'. It distinguishes from sibling tools like 'get_shaka_options' by focusing on documentation rather than configuration options, though it doesn't explicitly contrast them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_shaka_options' or 'run_shaka_packager', nor does it mention any prerequisites or exclusions. Usage is implied only by the tool's name and purpose, lacking explicit context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_shaka_optionsB
Get the available options and version information for Shaka Packager.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states what the tool does but fails to describe key traits: it doesn't specify if this is a read-only operation, what the output format looks like (though an output schema exists), or any potential side effects like network calls or authentication needs. This leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without any wasted words. It is front-loaded with the core action and resource, making it easy to parse and understand quickly. Every part of the sentence contributes essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (0 parameters, no annotations, but with an output schema), the description is minimally adequate. It explains what the tool does but lacks context on usage guidelines and behavioral traits. The presence of an output schema mitigates the need to describe return values, but more guidance on when and how to use this tool would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and the schema description coverage is 100%, so there are no parameters to document. The description appropriately doesn't add parameter details, as none are needed, aligning with the baseline for zero parameters. No compensation is required, and it avoids redundancy.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'available options and version information for Shaka Packager', making the purpose specific and understandable. However, it doesn't explicitly distinguish this tool from its sibling 'get_shaka_documentation', which might also provide information about Shaka Packager, leaving some ambiguity about differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_shaka_documentation' or 'run_shaka_packager'. It lacks context about prerequisites, such as whether Shaka Packager needs to be installed or configured, or any exclusions for usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
run_shaka_packagerC
Run a custom Shaka Packager command.
Args:
file_path: Path to the uploaded video file.
command_args: Additional arguments to pass to the shaka-packager command.
| Name | Required | Description | Default |
|---|---|---|---|
| file_path | Yes | ||
| command_args | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool runs a command but doesn't explain what Shaka Packager is, what the command does (e.g., video packaging, transcoding), potential side effects (e.g., file modifications), or any requirements like permissions or rate limits. This leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, with a clear purpose statement followed by a bullet-point list of parameters. It avoids unnecessary words and is front-loaded with the main action. However, it could be slightly more efficient by integrating parameter details into a single sentence without losing clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (running a custom command with two parameters), no annotations, and an output schema (which reduces the need to describe return values), the description is minimally complete. It covers the basic purpose and parameters but lacks behavioral context and usage guidelines, making it adequate but with clear gaps for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds basic semantics for both parameters ('file_path' and 'command_args'), explaining their purposes beyond the schema, which has 0% description coverage. However, it lacks details on formats (e.g., what 'command_args' should include) or constraints, providing only minimal value over the bare schema. With two parameters and low schema coverage, this is adequate but not comprehensive.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Run a custom Shaka Packager command.' This specifies the verb ('Run') and resource ('Shaka Packager command'), making it understandable. However, it doesn't differentiate from sibling tools like 'analyze_video' or 'get_shaka_options', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools or contexts where this is preferred, such as for custom packaging versus standard analysis or documentation retrieval. This lack of comparative usage information limits its helpfulness.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
4 tool updates
- First observed
analyze_video - First observed
get_shaka_documentation - First observed
get_shaka_options - First observed
run_shaka_packager
TDQS
Each tool has a clearly distinct purpose: analyze_video for file analysis, get_shaka_documentation for documentation retrieval, get_shaka_options for version/options info, and run_shaka_packager for custom command execution. There is no overlap or ambiguity between these functions.
All tools follow a consistent verb_noun pattern (analyze_video, get_shaka_documentation, get_shaka_options, run_shaka_packager) with clear, descriptive names. The naming convention is uniform throughout the set.
Four tools is reasonable for a Shaka Packager server, covering core functions like analysis, documentation, options, and execution. However, it feels slightly thin as it lacks tools for common specific operations like packaging or transmuxing, which might be expected in this domain.
The toolset covers basic Shaka Packager interactions but has notable gaps. It provides analysis, documentation, options, and custom execution, but lacks dedicated tools for standard packaging workflows (e.g., create_manifest, package_video) that would complete the surface for media processing tasks.
Maintenance
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