MCP Audio Tweaker
Provides optimized preset for processing ElevenLabs AI voice output, including audio normalization and format conversion tailored for AI-generated voice files.
Leverages FFmpeg for robust audio processing including sample rate conversion, bitrate adjustment, volume control, channel configuration, and audio effects with support for multiple formats (MP3, WAV, OGG, FLAC, M4A, AAC).
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., "@MCP Audio Tweakerapply the elevenLabs-optimize preset to my voiceover.wav file"
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.
MCP Audio Tweaker
A Model Context Protocol (MCP) server for batch audio processing and optimization using FFmpeg. This package provides parameter-based audio modifications including sample rate conversion, bitrate adjustment, volume control, channel configuration, and audio effects.
Features
🎵 Comprehensive Audio Processing: Sample rate conversion, bitrate adjustment, volume control, channel configuration
🔧 FFmpeg Integration: Leverages FFmpeg for robust, cross-platform audio processing
📦 Batch Processing: Process multiple audio files concurrently with queue management
🎯 Preset System: Predefined configurations for common use cases (game audio, voice processing, music mastering)
🎮 Game Audio Optimized: Special presets for mobile, desktop, and console game development
🤖 ElevenLabs Integration: Optimized preset for ElevenLabs AI voice output
🔍 MCP Compatible: Full integration with Claude Desktop and other MCP clients
⚡ Concurrent Processing: Efficient queue-based processing for large batch operations
📊 Detailed Reporting: Comprehensive processing results and error handling
Related MCP server: FFmpeg MCP Tool
Installation
npm install -g mcp-audio-tweakerPrerequisites
Node.js 18.0.0 or higher
FFmpeg installed and available in system PATH
Installing FFmpeg
Windows:
# Using Chocolatey
choco install ffmpeg
# Using winget
winget install FFmpegmacOS:
# Using Homebrew
brew install ffmpegLinux:
# Ubuntu/Debian
sudo apt update && sudo apt install ffmpeg
# CentOS/RHEL
sudo yum install ffmpegQuick Start
MCP Integration with Claude Desktop
Add to your Claude Desktop configuration:
{
"mcpServers": {
"audio-tweaker": {
"command": "npx",
"args": ["-y", "mcp-audio-tweaker"],
"env": {
"AUDIO_TWEAKER_LOG_LEVEL": "info"
}
}
}
}Standalone Usage
Check system requirements:
mcp-audio-tweaker --standalone checkProcess a single file:
mcp-audio-tweaker --standalone process \
--input input.wav \
--output output.mp3 \
--volume -3 \
--sample-rate 44100 \
--bitrate 192 \
--normalizeBatch process with preset:
mcp-audio-tweaker --standalone batch \
--input-dir ./audio/raw \
--output-dir ./audio/processed \
--preset game-audio-mobileList available presets:
mcp-audio-tweaker --standalone presetsMCP Tools
process_audio_file
Process a single audio file with custom operations.
Parameters:
inputFile(string): Path to input audio fileoutputFile(string): Path for output fileoperations(object): Audio processing operationsoverwrite(boolean): Whether to overwrite existing files
Example:
{
"inputFile": "/path/to/input.wav",
"outputFile": "/path/to/output.mp3",
"operations": {
"volume": {
"adjust": -3,
"normalize": true,
"targetLUFS": -20
},
"format": {
"sampleRate": 44100,
"bitrate": 192,
"channels": 2,
"codec": "mp3"
},
"effects": {
"fadeIn": 0.1,
"fadeOut": 0.2
}
}
}batch_process_audio
Process multiple audio files in a directory.
Parameters:
inputDirectory(string): Directory containing input filesoutputDirectory(string): Directory for processed filesfilePattern(string): Glob pattern for file matchingoperations(object): Audio processing operationsoverwrite(boolean): Whether to overwrite existing files
apply_preset
Apply predefined audio processing preset.
Parameters:
inputFile(string): Path to input audio fileoutputFile(string): Path for output filepreset(string): Preset name to applyoverwrite(boolean): Whether to overwrite existing files
Available Presets:
game-audio-mobile: Optimized for mobile gamesgame-audio-desktop: High-quality for desktop gamesgame-audio-console: Premium quality for consoleselevenLabs-optimize: Optimizes ElevenLabs AI voice outputvoice-processing: General voice and dialogue processingmusic-mastering: High-quality music masteringsfx-optimization: Sound effects and ambient audio
list_presets
List all available presets with descriptions.
Parameters:
category(string, optional): Filter by category (game,voice,music,effects)
get_queue_status
Get current status of the audio processing queue.
Audio Operations
Volume Operations
{
"volume": {
"adjust": -3, // Volume adjustment in dB (-60 to +20)
"normalize": true, // Apply loudness normalization
"targetLUFS": -23 // Target LUFS for normalization
}
}Format Operations
{
"format": {
"sampleRate": 44100, // Sample rate (8000, 16000, 22050, 44100, 48000, 96000, 192000)
"bitrate": 192, // Bitrate in kbps (64-320)
"channels": 2, // Channel count (1, 2, 6, 8)
"codec": "mp3" // Codec (pcm, mp3, aac, vorbis, flac)
}
}Effects Operations
{
"effects": {
"fadeIn": 0.1, // Fade in duration in seconds
"fadeOut": 0.2, // Fade out duration in seconds
"trim": { // Trim audio
"start": 1.0, // Start time in seconds
"end": 30.0 // End time in seconds
},
"loop": { // Loop audio
"enabled": true,
"count": 3 // Number of loops
}
}
}Claude Desktop Usage Examples
Optimize ElevenLabs Voice Output
@audio-tweaker Apply the elevenLabs-optimize preset to the file /audio/voice-output.wav and save it as /audio/optimized-voice.mp3Batch Process Game Audio
@audio-tweaker Process all WAV files in /game-assets/audio/raw/ using the game-audio-mobile preset and save them to /game-assets/audio/mobile/Custom Voice Processing
@audio-tweaker Process /recordings/dialogue.wav with the following operations: normalize audio to -20 LUFS, convert to 22kHz mono MP3 at 128kbps, add 0.05s fade in and 0.1s fade out, and save as /processed/dialogue.mp3Check Audio Processing Status
@audio-tweaker What's the current status of the audio processing queue?Workflow Integration
Game Development Workflow
Generate AI Voice with ElevenLabs
Optimize with MCP Audio Tweaker: Apply
elevenLabs-optimizepresetPlatform-specific Processing: Use
game-audio-mobile,game-audio-desktop, orgame-audio-consolepresetsIntegration: Import optimized audio into game engine
Music Production Workflow
Record/Import Audio
Master with Audio Tweaker: Apply
music-masteringpresetPlatform Optimization: Create platform-specific versions
Distribution: Export in required formats
Configuration
Environment Variables
AUDIO_TWEAKER_LOG_LEVEL: Set logging level (debug,info,warn,error)FFMPEG_PATH: Custom FFmpeg binary path (optional)
Advanced Configuration
The package supports advanced FFmpeg configurations through direct parameter passing. See the FFmpeg documentation for additional options.
Error Handling
The package provides comprehensive error handling with specific error codes:
FILE_NOT_FOUND: Input file does not existFFMPEG_NOT_FOUND: FFmpeg not installed or not in PATHINVALID_PARAMETERS: Processing parameters validation failedOUTPUT_WRITE_FAILED: Cannot write to output locationPROCESSING_FAILED: FFmpeg processing failedPRESET_NOT_FOUND: Requested preset does not exist
Performance
Concurrent Processing: Default 2 concurrent operations (configurable)
Queue Management: Efficient processing queue with pause/resume capabilities
Memory Efficient: Streams audio data without loading entire files into memory
Cross-platform: Optimized for Windows, macOS, and Linux
Supported Formats
Input Formats: MP3, WAV, OGG, FLAC, M4A, AAC Output Formats: MP3, WAV, OGG, FLAC, M4A, AAC
Development
Building from Source
git clone https://github.com/your-org/mcp-audio-tweaker.git
cd mcp-audio-tweaker
npm install
npm run buildRunning Tests
npm test
npm run test:coverage
npm run test:ffmpegContributing
Fork the repository
Create a feature branch
Make your changes
Add tests for new functionality
Submit a pull request
Complete Documentation
This README provides a quick overview. For comprehensive documentation:
🚀 Getting Started
Installation Guide: Complete setup instructions
Quick Start Tutorial: Get running in 15 minutes
API Reference: Complete API documentation
🔧 Support & Troubleshooting
Troubleshooting Guide: Common issues and solutions
Contributing Guide: How to contribute to the project
License
MIT License - see LICENSE file for details.
Support
Issues: GitHub Issues
Documentation: README
Community: Discussions
Acknowledgments
Built with FFmpeg for audio processing
Uses Model Context Protocol for Claude Desktop integration
Designed for Infinity Cube game audio workflow
Available Tools
9 toolsadvanced_processC
Apply advanced audio processing including pitch shifting, spectral processing, dynamics, and spatial effects
| Name | Required | Description | Default |
|---|---|---|---|
| inputFile | Yes | Path to input audio file | |
| outputFile | Yes | Path for output file | |
| pitch | No | Pitch shifting operations | |
| tempo | No | Tempo adjustment operations | |
| spectral | No | Spectral processing operations | |
| dynamics | No | Dynamics processing operations | |
| spatial | No | Spatial processing operations | |
| overwrite | No | Whether to overwrite existing output files |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While 'Apply advanced audio processing' implies a transformative operation, it doesn't disclose critical behaviors: whether processing is destructive to the original file, computational requirements, supported audio formats, error handling, or typical processing time. The description mentions effect categories but not how they're applied or sequenced.
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. Every word contributes meaning by listing the four processing categories. However, it could be slightly more structured by separating the tool's primary function from its capabilities.
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?
For a complex audio processing tool with 8 parameters (including nested objects), no annotations, and no output schema, the description is inadequate. It doesn't explain what the tool returns (success/failure, processing metadata, error messages), doesn't address performance characteristics, and provides minimal guidance for a tool with substantial parameter complexity and multiple sibling alternatives.
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?
With 100% schema description coverage, the schema already documents all 8 parameters thoroughly. The description adds minimal value beyond the schema by naming the processing categories (pitch, spectral, dynamics, spatial) that correspond to optional parameter objects, but doesn't provide additional context about parameter interactions, default behaviors when optional params are omitted, or processing order.
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 specific verbs ('Apply advanced audio processing') and resources ('audio'), listing key processing categories (pitch shifting, spectral processing, dynamics, spatial effects). However, it doesn't explicitly differentiate this from sibling tools like 'process_audio_file' or 'apply_preset', which likely handle similar audio processing tasks.
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. With siblings like 'process_audio_file', 'apply_preset', and 'batch_process_audio', there's no indication whether this is for complex multi-effect processing, real-time vs batch operations, or when simpler tools might suffice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
apply_presetC
Apply predefined audio processing preset optimized for specific use cases
| Name | Required | Description | Default |
|---|---|---|---|
| inputFile | Yes | Path to input audio file | |
| outputFile | Yes | Path for output file | |
| preset | Yes | Preset name to apply | |
| overwrite | No | Whether to overwrite existing output files |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but lacks critical behavioral details. It doesn't disclose whether this is a read-only or destructive operation, what happens if the output file exists (beyond the 'overwrite' parameter), performance characteristics, or error conditions. The description adds minimal context beyond the basic action.
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 states the core purpose without unnecessary words. It's appropriately sized for the tool's complexity and gets straight to the point with zero waste.
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?
For a tool with 4 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what the tool returns, what happens during processing, error handling, or performance expectations. The mention of 'optimized for specific use cases' is too vague to be helpful without elaboration.
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?
With 100% schema description coverage, the schema already documents all 4 parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema - it doesn't explain what the presets do, provide examples, or clarify relationships between parameters. Baseline 3 is appropriate when schema does the heavy lifting.
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 'apply' and the resource 'predefined audio processing preset', specifying it's optimized for specific use cases. It distinguishes from siblings like 'process_audio_file' by focusing on preset application rather than general processing, though it doesn't explicitly name alternatives.
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?
No guidance is provided on when to use this tool versus alternatives like 'process_audio_file' or 'advanced_process'. The description mentions 'optimized for specific use cases' but doesn't specify what those cases are or when to choose this over other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
batch_process_audioC
Apply audio processing operations to multiple files in a directory
| Name | Required | Description | Default |
|---|---|---|---|
| inputDirectory | Yes | Directory containing input files | |
| outputDirectory | Yes | Directory for processed files | |
| filePattern | No | Glob pattern for file matching | *.{mp3,wav,ogg,flac,m4a,aac} |
| operations | Yes | Audio processing operations to apply (same as process_audio_file) | |
| overwrite | No | Whether to overwrite existing output files |
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 'apply audio processing operations' which implies mutation/write operations, but doesn't disclose critical behaviors like whether it processes files sequentially or in parallel, error handling, progress tracking, or resource usage. The mention of 'overwrite' parameter hints at destructive potential, but this isn't elaborated in the description itself.
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 unnecessary words. It's appropriately sized and front-loaded with the core functionality.
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?
For a batch processing tool with 5 parameters, nested objects, no annotations, and no output schema, the description is inadequate. It doesn't explain what 'audio processing operations' entail, how results are returned, error behavior, or performance characteristics. The context signals indicate complexity that isn't addressed in the minimal description.
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?
Schema description coverage is 100%, so the schema already documents all 5 parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't explain the 'operations' object structure or provide examples). Baseline 3 is appropriate when the schema does the heavy lifting.
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 'apply' and resource 'audio processing operations to multiple files in a directory', which is specific and actionable. However, it doesn't explicitly distinguish this batch processing tool from its sibling 'process_audio_file' (single-file processing), which would be needed for 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 like 'process_audio_file' (for single files) or other audio processing siblings. It mentions 'multiple files in a directory' but doesn't specify thresholds, prerequisites, or exclusions for batch versus single-file processing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_harmonicsC
Create harmonic variations by adding octaves and musical intervals
| Name | Required | Description | Default |
|---|---|---|---|
| inputFile | Yes | Path to input audio file | |
| outputDirectory | Yes | Directory for harmonic variations | |
| octaveUp | No | Mix level for octave up (0-1) | |
| octaveDown | No | Mix level for octave down (0-1) | |
| fifthUp | No | Mix level for perfect fifth up (0-1) | |
| thirdUp | No | Mix level for major third up (0-1) | |
| overwrite | No | Whether to overwrite existing output files |
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. While 'create' implies a write operation, it doesn't specify whether this is a destructive or safe process, what permissions might be required, or how errors are handled. The description lacks details on output behavior, file formats, or any side effects, which is a significant gap for a tool with no annotation coverage.
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 fluff or redundancy. It's front-loaded with the core action and method, making it easy to parse quickly.
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?
For a tool with 7 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what 'harmonic variations' output looks like (e.g., file types, naming conventions), how the process works, or any prerequisites. Given the complexity and lack of structured data, more context is needed for the agent to use this tool effectively.
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?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds no additional parameter information beyond what's in the schema, such as explaining how the mix levels interact or what 'harmonic variations' entail. Baseline 3 is appropriate when the schema does the heavy lifting.
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 ('create harmonic variations') and the method ('by adding octaves and musical intervals'), which is specific and actionable. However, it doesn't explicitly differentiate this tool from sibling tools like 'generate_variations' or 'process_audio_file', which might have overlapping functionality in audio processing.
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. With siblings like 'generate_variations', 'process_audio_file', and 'advanced_process', there's no indication of what makes this tool unique or when it's the appropriate choice, leaving the agent to guess based on tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_variationsC
Generate multiple variations of a sound from a single input - perfect for creating sound families
| Name | Required | Description | Default |
|---|---|---|---|
| inputFile | Yes | Path to input audio file | |
| outputDirectory | Yes | Directory for output variations | |
| count | No | Number of variations to generate (1-20) | |
| pitchRange | No | Pitch variation range in semitones (±) | |
| volumeRange | No | Volume variation range in dB (±) | |
| spectralRange | No | Spectral variation range in dB (±) | |
| seed | No | Random seed for reproducible variations | |
| overwrite | No | Whether to overwrite existing output files |
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 mentions the tool generates variations but lacks details on permissions, rate limits, file formats, error handling, or output specifics (e.g., file naming, format). This is inadequate for a tool with 8 parameters and file operations, leaving significant gaps in understanding its 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 front-loads the core purpose. It wastes no words and is appropriately sized for the tool's complexity, making it easy for an agent to parse quickly.
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 (8 parameters, file operations, no annotations, no output schema), the description is insufficient. It doesn't cover behavioral aspects like file handling, output details, or error conditions. While concise, it fails to provide the completeness needed for an agent to confidently invoke this tool without additional context.
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 100%, so all parameters are documented in the schema. The description adds no additional parameter semantics beyond implying variation generation. It doesn't explain how parameters like 'pitchRange' or 'spectralRange' interact or affect the output, so it relies entirely on the schema, meeting the baseline for high coverage.
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: 'Generate multiple variations of a sound from a single input'. It specifies the verb ('generate'), resource ('variations of a sound'), and outcome ('creating sound families'). However, it doesn't explicitly differentiate from sibling tools like 'batch_process_audio' or 'process_audio_file', which might have overlapping functionality.
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 minimal usage guidance: 'perfect for creating sound families' suggests a use case but doesn't specify when to use this tool versus alternatives like 'batch_process_audio' or 'create_harmonics'. No explicit when-not-to-use scenarios or prerequisites are mentioned, leaving the agent with little contextual direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_queue_statusB
Get current status of the audio processing queue
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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. It states it 'gets' status, implying a read-only operation, but doesn't disclose behavioral traits such as whether it requires authentication, returns real-time or cached data, includes error states, or has rate limits. For a status-checking tool with zero annotation coverage, this leaves significant gaps in understanding its 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 front-loads the core purpose without any wasted words. It's appropriately sized for a simple status-checking tool, making it easy to parse and understand quickly.
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, no output schema), the description is minimally adequate. However, without annotations or output schema, it lacks details on what the status includes (e.g., queue length, processing times, errors) or behavioral context. For a status tool, this leaves room for improvement in 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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate here. A baseline of 4 is applied for tools with zero parameters, as there's nothing to compensate for.
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 resource ('current status of the audio processing queue'), making the purpose unambiguous. It doesn't explicitly distinguish from sibling tools like 'list_presets' or 'batch_process_audio', but the focus on queue status is specific enough to avoid confusion with those operations.
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 prerequisites (e.g., whether audio processing must be active), exclusions, or how it differs from sibling tools like 'process_audio_file' or 'advanced_process' in terms of queue monitoring versus processing actions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
layer_soundsC
Layer multiple sounds together with advanced blending and timing
| Name | Required | Description | Default |
|---|---|---|---|
| inputFiles | Yes | Array of input file paths to layer | |
| outputFile | Yes | Path for output file | |
| layers | Yes | Layer configuration for each input | |
| overwrite | No | Whether to overwrite existing output files |
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 mentions 'advanced blending and timing' but fails to detail critical aspects like file format requirements, performance constraints, error handling, or output characteristics. For a tool with 4 parameters and file operations, this is a significant gap in transparency.
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 functionality ('Layer multiple sounds together') and adds key details ('with advanced blending and timing') without unnecessary elaboration. Every word earns its place, making it highly concise and well-structured.
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 (4 parameters, file operations, no annotations, and no output schema), the description is insufficient. It lacks details on output format, error conditions, or integration with sibling tools, leaving gaps that could hinder effective agent usage in a multi-tool audio processing context.
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 100%, so the schema fully documents all parameters. The description adds no additional meaning beyond the schema, such as explaining how 'blend' modes interact or the practical effects of 'delay' and 'pitch.' This meets the baseline for high schema coverage but doesn't enhance understanding.
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 as 'Layer multiple sounds together with advanced blending and timing,' which specifies the verb ('layer') and resource ('sounds') with additional context about capabilities. However, it doesn't explicitly differentiate from sibling tools like 'batch_process_audio' or 'process_audio_file,' which may have overlapping audio processing functions.
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 lacks context about specific scenarios, prerequisites, or comparisons to sibling tools such as 'apply_preset' or 'generate_variations,' leaving the agent without clear usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_presetsC
List all available audio processing presets with their descriptions
| Name | Required | Description | Default |
|---|---|---|---|
| category | No | Filter presets by category |
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 it lists presets, implying a read-only operation, but doesn't cover aspects like whether it requires authentication, rate limits, pagination, or error handling. This leaves significant gaps for a tool with no annotation support.
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 appropriately sized and front-loaded, making it easy to understand at a glance.
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 no annotations and no output schema, the description is incomplete. It doesn't explain what the output looks like (e.g., list format, included fields like preset names and descriptions), behavioral traits, or usage context. For a tool with rich sibling tools and no structured support, this is inadequate.
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 input schema has 100% description coverage, documenting the optional 'category' parameter with its enum values. The description adds no additional parameter semantics beyond what the schema provides, such as default behavior when no category is specified. Baseline 3 is appropriate as the schema does the heavy lifting.
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 ('List') and resource ('audio processing presets') with their descriptions, making the purpose specific and understandable. However, it doesn't explicitly differentiate this tool from potential siblings like 'apply_preset' or 'process_audio_file' beyond the listing action.
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?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites, such as needing presets to exist, or compare it to sibling tools like 'apply_preset' for applying presets or 'process_audio_file' for processing with presets.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
process_audio_fileC
Apply audio processing operations to a single file using FFmpeg
| Name | Required | Description | Default |
|---|---|---|---|
| inputFile | Yes | Path to input audio file | |
| outputFile | Yes | Path for output file | |
| operations | Yes | Audio processing operations to apply | |
| overwrite | No | Whether to overwrite existing output files |
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 mentions 'Apply audio processing operations' and 'using FFmpeg', which hints at mutation and external tool usage, but doesn't specify critical behaviors like whether it modifies files in-place, requires specific permissions, handles errors, or has performance constraints. For a tool with complex operations and no annotations, this is a significant gap in transparency.
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 ('Apply audio processing operations to a single file using FFmpeg'). It wastes no words and is appropriately sized for the tool's complexity, making it easy to parse 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 complexity (4 parameters with nested objects, no output schema, and no annotations), the description is incomplete. It doesn't explain the output format, error handling, or behavioral traits like file system interactions or FFmpeg dependencies. With rich input schema but missing critical context for a mutation tool, the description fails to provide enough information for safe and effective 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 schema description coverage is 100%, with detailed descriptions for parameters like 'inputFile', 'outputFile', and 'overwrite', and nested objects for 'operations'. The description adds minimal value beyond the schema, as it only vaguely references 'audio processing operations' without explaining the structure or purpose of the 'operations' object. Given the high schema coverage, the baseline score of 3 is appropriate, as the description doesn't significantly enhance parameter understanding.
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 ('Apply audio processing operations') and resource ('to a single file using FFmpeg'), making the purpose understandable. However, it doesn't differentiate this tool from siblings like 'advanced_process', 'batch_process_audio', or 'apply_preset', which likely offer similar or overlapping functionality. The description is specific but lacks sibling distinction.
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. With siblings like 'advanced_process', 'batch_process_audio', and 'apply_preset', an agent needs explicit direction on choosing this tool for single-file FFmpeg processing over others. The description implies usage for audio processing but offers no context about prerequisites, limitations, or comparisons to sibling tools.
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.
9 tool updates
v1.0.0- First observed
advanced_process - First observed
apply_preset - First observed
batch_process_audio - First observed
create_harmonics - First observed
generate_variations - First observed
get_queue_status - First observed
layer_sounds - First observed
list_presets - First observed
process_audio_file
TDQS
Most tools have distinct purposes, but 'advanced_process' and 'process_audio_file' could cause confusion since both handle audio processing operations. The descriptions help differentiate them (advanced vs. single-file FFmpeg-based), but the overlap in core functionality creates some ambiguity.
All tools follow a consistent snake_case verb_noun pattern (e.g., 'apply_preset', 'batch_process_audio', 'layer_sounds'). The naming is predictable and readable throughout the set, with no deviations in style.
With 9 tools, the count is well-scoped for an audio processing server. Each tool appears to serve a specific and useful function in the domain, from basic processing to advanced features like harmonics and variations, without feeling bloated or thin.
The tool set covers core audio processing workflows well, including single and batch processing, presets, sound layering, and queue management. A minor gap exists in lacking explicit tools for audio analysis or metadata handling, but agents can likely work around this with the provided operations.
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