mcp-audio-analysis

by hugohow

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes in audio analysis (e.g., beat tracking vs. chroma vs. MFCC), but download_from_url and download_from_youtube overlap significantly in function—both download audio files from different sources with similar descriptions. The core analysis tools are well-differentiated, but the download tools could cause confusion.
Naming Consistency3/5
The naming is mixed: some tools use descriptive verb_noun patterns (beat_track, get_duration), while others are single verbs (load, tempo) or noun phrases (chroma_cqt, mfcc). There's no consistent convention across all tools, though most names are readable and hint at their function.
Tool Count4/5
With 8 tools, the count is reasonable for an audio analysis server, covering key operations like loading, downloading, and various analysis features. It's slightly lean but not incomplete, as it includes essential functions without being overwhelming.
Completeness3/5
The server covers basic audio analysis tasks (loading, downloading, duration, tempo, spectral features), but there are notable gaps: no tools for editing, filtering, or exporting audio, and no way to visualize results. The analysis tools are focused on computation but lack broader workflow support.
Average 3/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
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- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
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 the tool computes MFCC using librosa and notes 'It's sometimes better to take harmonics only', which adds some context about input considerations. However, it lacks critical behavioral details such as what the output looks like (e.g., MFCC coefficients as an array), performance characteristics, or any error handling, leaving significant gaps for a tool with computational implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is moderately concise with three sentences, but it could be more front-loaded. The first sentence clearly states the action, but the second sentence about MFCC representation is somewhat redundant with the first. The third sentence adds parameter details, which is useful but disrupts flow. Overall, it's not wasteful but lacks optimal structure for quick comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a single parameter with low schema coverage, the description is incomplete. It explains the parameter well but fails to describe the output (e.g., what MFCC data is returned), which is critical for a computational tool. Without this, an agent cannot fully understand how to use the results, making the context insufficient for effective tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter with 0% description coverage, so the description must compensate. It explains 'path_audio_time_series_y' as 'The path to the audio time series (CSV file)' and adds the heuristic 'It's sometimes better to take harmonics only', which provides meaningful semantic context beyond the schema's basic type. This adequately clarifies the parameter's purpose and usage nuance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool 'Computes the MFCC of the given audio time series using librosa' and mentions it's 'useful for music analysis', which provides a basic purpose. However, it doesn't clearly distinguish this from sibling tools like 'chroma_cqt' or 'tempo' which also analyze audio features, making the differentiation vague. The purpose is understandable but lacks specificity about what makes MFCC unique compared to alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 sibling tools such as 'beat_track' or 'chroma_cqt'. It mentions MFCC is 'useful for music analysis', but this is too general and doesn't help an agent decide between similar audio processing tools. There are no explicit when/when-not instructions or alternatives named, leaving usage unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'estimates' and 'using librosa,' implying a read-only analysis, but lacks details on behavioral traits such as performance characteristics, error handling, or output format. It doesn't disclose whether this is computationally intensive, if it requires specific audio formats, or what the result looks like beyond BPM.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences, front-loaded with the core purpose. It avoids redundancy, but the second sentence about 'offset and duration' is misleading as it doesn't align with the actual parameters, slightly reducing efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 6 parameters with 0% schema coverage, no annotations, and no output schema, the description is incomplete. It doesn't explain the input parameters, expected output (beyond BPM), or behavioral context, making it inadequate for an AI agent to use the tool effectively without additional documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It only mentions 'offset and duration are optional, in seconds,' which doesn't map to any of the 6 parameters in the schema (e.g., 'path_audio_time_series_y,' 'hop_length'). This adds minimal meaning beyond the schema, failing to explain what parameters like 'std_bpm' or 'ac_size' do, leaving most semantics undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Estimates the tempo (in BPM) of the given audio time series using librosa.' It specifies the verb ('estimates'), resource ('tempo of audio time series'), and method ('using librosa'), though it doesn't explicitly differentiate from siblings like 'beat_track' which might also relate to tempo analysis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal usage guidance: 'Offset and duration are optional, in seconds.' This hints at optional parameters but doesn't explain when to use this tool versus alternatives like 'beat_track' or other audio processing siblings, nor does it mention prerequisites or typical scenarios for tempo estimation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 the tool downloads a file and returns a path, which covers basic functionality, but lacks critical details: it doesn't specify file size limits, supported URL protocols, error handling, storage location, or whether it overwrites existing files. The warning about song names is vague and doesn't clarify behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief with two sentences, but the second sentence 'Be careful, you will never know the name of the song' is confusing and doesn't add clear value, reducing efficiency. The first sentence is front-loaded and informative, but overall structure could be improved by removing or clarifying the cryptic warning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and low schema coverage, the description is incomplete for a download tool. It lacks details on return values (e.g., path format), error conditions, supported file types, or security considerations. The sibling tools suggest audio processing context, but the description doesn't explain how this fits into that workflow.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, so the description must compensate. It mentions 'a given URL', which adds meaning to the 'url' parameter by indicating it should be a downloadable URL. However, it doesn't provide details on URL format requirements, validation, or examples. With one parameter and low schema coverage, this is adequate but minimal.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Downloads') and resource ('a file from a given URL'), specifying what the tool does. It distinguishes from siblings like 'download_from_youtube' by not being platform-specific. However, it doesn't explicitly differentiate from other download tools beyond the URL source.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'download_from_youtube' or 'load'. The cryptic warning 'Be careful, you will never know the name of the song' is unclear and doesn't offer practical usage context. No explicit when/when-not instructions or prerequisites are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 returns a duration in seconds, but doesn't describe error handling (e.g., for invalid file paths), performance characteristics, or what constitutes a valid 'audio time series'. For a 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that efficiently communicates the core functionality. It's front-loaded with the key action ('Returns') and includes essential details (unit of measurement) without unnecessary elaboration. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (1 parameter with 0% schema coverage, no annotations, no output schema), the description is incomplete. It doesn't explain the return format beyond 'in seconds' (e.g., numeric value, error cases), parameter requirements, or how it differs from related audio processing tools. For a tool with minimal structured data, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for undocumented parameters. It mentions 'the given audio time series' which relates to the single parameter, but doesn't explain what 'path_audio_time_series_y' represents (e.g., file path format, expected data structure). The description adds minimal semantic value beyond what's inferable from the parameter name.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 ('Returns') and resource ('total duration of the given audio time series'), including the unit of measurement ('in seconds'). It distinguishes itself from siblings by focusing on duration calculation rather than audio processing tasks like beat tracking or feature extraction. However, it doesn't explicitly differentiate from all siblings (e.g., 'tempo' also relates to timing).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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., needing an audio time series file), exclusions, or comparisons to sibling tools like 'tempo' (which might provide timing-related information). Usage is implied through the parameter name but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 a caution about not knowing the song name, which hints at limitations, but fails to describe critical behaviors such as file format, download location, error handling, or performance traits. For a download tool with zero annotation coverage, this leaves significant gaps in understanding how it operates.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with the core functionality in the first sentence. The second sentence adds a caution but could be more integrated. Overall, it's efficient with minimal waste, though the warning feels slightly tacked on rather than seamlessly structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a download operation, no annotations, no output schema, and low schema coverage, the description is incomplete. It lacks details on output format (e.g., what the 'path' entails), error conditions, dependencies, or side effects. The caution about song names is insufficient to cover the tool's full context and usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 explains that the parameter 'youtube_url' is used to download a file, adding meaning beyond the schema's basic type definition. However, it doesn't detail URL format requirements, validation rules, or examples, leaving some semantic gaps for the single parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Downloads a file from a given youtube URL and returns the path to the downloaded file.' It specifies the verb ('downloads'), resource ('file from a given youtube URL'), and output ('returns the path'). However, it doesn't explicitly differentiate from sibling tools like 'download_from_url' beyond the YouTube-specific context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal guidance: 'Be careful, you will never know the name of the song.' This is a vague warning rather than clear usage instructions. It doesn't specify when to use this tool versus alternatives like 'download_from_url' or other siblings, nor does it outline prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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. It explains what the tool does and lists parameters, but doesn't describe output format, error conditions, performance characteristics, or any side effects. For a computational tool with 5 parameters, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized. It starts with the core purpose, adds context about usefulness, then details parameters in a clear bulleted format. Each sentence earns its place, though the parameter explanations could be slightly more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters with 0% schema coverage and no output schema, the description does a decent job explaining the tool's purpose and parameters. However, it lacks crucial information about return values, error handling, and practical usage examples that would be needed for complete understanding of this computational tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds substantial value beyond the schema, which has 0% description coverage. It explains what 'hop_length', 'start_bpm', 'tightness', and 'units' mean conceptually (e.g., 'tightness of the beat tracking', 'units of the beat track'), providing semantic context that the bare schema titles lack. However, it doesn't fully cover all parameters or provide detailed usage examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'computes the beat track of the given audio time series using librosa' and explains it's 'useful for music analysis', providing a specific verb (computes) and resource (beat track). However, it doesn't explicitly differentiate from sibling tools like 'tempo' which might be related to rhythmic analysis, leaving room for improvement in sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'tempo' or 'mfcc' for music analysis. It mentions the tool's purpose but offers no context about when it's appropriate or what scenarios it's best suited for, leaving the agent without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses that it loads files and returns a path, and includes a behavioral warning about not identifying song names. However, it lacks details on error handling (e.g., invalid file paths), performance aspects (e.g., file size limits), or output format specifics beyond 'path to audio time series', leaving gaps for a mutation-like tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with three sentences: the first states the core purpose, the second adds parameter context, and the third provides a critical warning. It's front-loaded with the main action, but the warning could be more integrated; overall, it's efficient with little waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and 3 parameters with 0% schema coverage, the description is moderately complete. It covers the basic operation and key parameters but lacks details on output (beyond 'path'), error cases, or integration with siblings like 'beat_track'. For a tool that likely mutates state (loading files), more behavioral context would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds meaning by explaining that offset and duration are 'optional, in seconds', which clarifies their units and optionality beyond the schema's default values. However, it doesn't detail the 'file_path' parameter (e.g., format or constraints), leaving one of three parameters with minimal semantic enhancement.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'loads' and resource 'audio file', specifying it returns 'the path to the audio time series'. It distinguishes from siblings like 'download_from_url' or 'get_duration' by focusing on loading local files for audio processing. However, it doesn't explicitly differentiate from all siblings (e.g., 'mfcc' or 'chroma_cqt' which might also process audio).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for loading audio files with optional offset/duration, and the warning 'you will never know the name of the song' suggests it's for audio analysis rather than identification. However, it lacks explicit guidance on when to use this versus alternatives like 'download_from_url' for remote files or 'get_duration' for metadata, and doesn't mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses that the tool saves output to a CSV file and returns the file path, which is useful behavioral context. However, it doesn't mention performance characteristics, memory usage, error conditions, or whether the operation is read-only/destructive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and well-structured with clear sections: purpose, parameters, and output format. Every sentence adds value, though the parameter explanations could be slightly more concise. It's front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters with 0% schema coverage and no output schema, the description does an excellent job explaining parameters and output format. It could improve by mentioning computational requirements or typical use cases, but it's largely complete for this audio processing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate fully. It provides detailed explanations for all 5 parameters beyond just their names, including practical advice ('It's sometimes better to take harmonics only' for path_audio_time_series_y) and default values. This adds significant meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool computes chroma CQT from audio time series using librosa for music analysis. It specifies the verb 'computes' and resource 'chroma CQT', but doesn't explicitly differentiate from sibling tools like mfcc or tempo which are also audio analysis tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions chroma CQT is 'useful for music analysis' but provides no guidance on when to use this specific tool versus alternatives like mfcc or tempo. No explicit when/when-not statements or comparison to sibling tools are included.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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