Server Quality Checklist
- Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap. The four generation tools target different audio types (music, sfx, soundscape, voice), while utility tools handle distinct lifecycle phases (dependencies, configuration, cleanup, playback). Transition_soundscape is unambiguously a composite operation for scene changes.
Naming Consistency4/5Strong adherence to snake_case verb_noun pattern (generate_music, cleanup_assets, play_audio). The only deviation is 'configure' which lacks a noun object, though this is idiomatic for settings management. All generation tools use consistent 'generate_' prefix.
Tool Count5/5Nine tools is well-scoped for an audio generation server. The set covers four generation modes, configuration, dependency checking, playback, cleanup, and transitions without bloat. Each tool earns its place in the audio creation workflow.
Completeness4/5Covers the full generation lifecycle with creation, playback, configuration, and cleanup capabilities. Minor gap in asset inventory management—there is no tool to list or retrieve specific generated assets by ID, only bulk cleanup by age, though agents may track assets themselves.
Average 3.7/5 across 9 of 9 tools scored.
See the tool scores section below for per-tool breakdowns.
This repository includes a README.md file.
This repository includes a LICENSE file.
Latest release: v0.1.0
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This repository includes a glama.json configuration file.
- This server provides 9 tools. View schema
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Tool Scores
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses use of Gemini 2.0 Live model but omits other behavioral traits (rate limits, side effects, async nature) since annotations are absent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Compact three-sentence structure front-loaded with action, no redundancy, every sentence adds distinct value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for basic invocation but leaves technical audio parameters unexplained given the moderate complexity of the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 57% schema coverage and missing descriptions for bitrate/sample_rate/channels, description fails to compensate for these technical audio parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it generates environmental soundscapes with specific examples, and distinguishes from siblings via 'background ambience' and 'complex layered textures' (vs music/SFX/voice).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage context via 'Best for background ambience' but lacks explicit when-not-to-use or alternative tool references.
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?
States what gets checked (installed/accessible) but lacks details on failure behavior or return structure since no annotations exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single front-loaded sentence with strong verb, no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for simple tool but omits what constitutes success/failure without output schema to reference.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Zero parameters per schema establishes baseline 4; no parameter semantics needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clear specific action (verifies external tools) with concrete example (FFmpeg), functionally distinct from audio generation siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to invoke versus alternatives, or that it should precede generation tools requiring FFmpeg.
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?
Discloses persistence and dual read/write modes, but lacks details on validation, side effects, or impact on concurrent operations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose; every clause provides necessary guidance without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for basic invocation but omits return value structure (no output schema exists) and valid parameter ranges.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Partially compensates for 43% schema coverage by grouping parameters into semantic categories (format, sample rate, cleanup), but omits duration and transition parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clear action (view/update) and resource (persistent server settings) with specific examples that distinguish it from audio generation siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance for the empty-args viewing case but lacks explicit exclusions or alternatives versus sibling tools.
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?
Discloses execution mechanism (system default player like 'afplay') but omits critical behavioral details like blocking vs. async behavior, error handling, or supported formats since no annotations exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single, efficient sentence that front-loads the verb and mechanism; no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple single-parameter tool; explains the playback mechanism sufficiently given no output schema exists to document.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, baseline is met; description reinforces 'local' constraint but adds no substantial semantic layer beyond the schema's 'absolute path' definition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it plays local audio files using the system default player, effectively distinguishing from sibling generation tools (generate_music, generate_sfx, etc.).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage for existing files via 'local audio file,' but lacks explicit when/when-not guidance contrasting with the generation siblings.
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?
Discloses pricing ($0.08/$0.04) which is critical for paid models, but missing return value info, file persistence details, and rate limits (no annotations provided to cover these).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise and front-loaded; every sentence earns its place, though brevity comes at cost of missing behavioral details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Critical gap: no output schema exists and description fails to explain what is returned (file path, URL, binary data?) or auto_play behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 75% and adequately describes parameters; description adds minimal semantic value beyond schema except reinforcing the pricing model.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it generates songs/loops/segments and distinguishes from siblings (generate_sfx, generate_voice, generate_soundscape) by specifying 'melodic content, rhythm, and structured compositions'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
'Best for melodic content...' provides positive guidance for selection, though lacks explicit 'when not to use' or direct sibling comparisons.
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?
No annotations provided; description mentions 'smooth crossfade' but omits critical behavioral details like output format, file persistence, or side effects given the auto_play parameter.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences; front-loaded with core action, no redundancy, every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for basic invocation but incomplete given lack of output schema and annotations; omits return value description and optional parameter implications (format, auto_play).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With only 40% schema coverage, description implicitly clarifies from_prompt/to_prompt via 'two distinct soundscapes' but provides no semantic context for format, transition_duration, or auto_play.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Specifically states it generates two soundscapes with a crossfade transition, clearly distinguishing from sibling generate_soundscape (single static) and play_audio.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides implied usage context ('Ideal for evolving scenes') but lacks explicit when-not-to-use guidance or comparison to single soundscape generation.
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?
Discloses underlying model (Gemini 2.5 Native Audio) hinting at capabilities, but omits side effects, persistence, rate limits, or resource management details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely compact three-sentence structure with no redundancy; immediately establishes function and optimal use cases.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequately covers purpose and implementation for a straightforward 4-parameter tool, though return value format remains unspecified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema is fully self-documenting (100% coverage); description adds no parameter-specific semantics but meets baseline expectations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clear specific action (generates speech/narration) and target content (scripts, dialogue), though explicit differentiation from sibling audio generators is implied rather than stated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides positive usage guidance ('Best for scripts, character dialogue, and narration') but lacks explicit exclusions or references to alternative tools like generate_music.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but description compensates by disclosing specific model (Lyria-3-clip-preview) and pricing ($0.04/req), adding crucial operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three tightly constructed sentences: purpose definition, usage guidance, and cost disclosure—each earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for tool complexity but missing return value specification (critical given no output schema exists to indicate what the tool produces).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 67% schema coverage, description adds no parameter semantics; fails to explain undocumented 'auto_play' parameter or clarify expected prompt structure beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clear specific verbs ('generates isolated, short-duration sound effects and foley') with concrete examples, and implicitly distinguishes from siblings (generate_music, generate_soundscape) via 'one-shot' and 'isolated' qualifiers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
'Best for specific one-shot audio cues' provides clear contextual guidance for when to select this over sibling audio tools, though lacks explicit 'when not to use' exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Effectively discloses destructive deletion behavior and manual nature without annotations, though omits irreversibility warnings.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single, well-structured sentence front-loaded with action; no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequately covers the simple operation given low complexity, though could clarify if deletion affects all asset types or specific formats.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Meets baseline since schema has 100% description coverage; description mirrors but does not expand parameter semantics beyond 'certain age (in hours)'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Specific verb (deletion) and resource (generated audio assets) clearly distinguish this maintenance tool from sibling generation and playback tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context (manual trigger to save disk space) but lacks explicit when-not guidance or alternative comparisons.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
GitHub Badge
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- Confirm that the MCP server is working as expected.
- Confirm that there are no obvious security issues.
- Evaluate tool definition quality.
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However, if the MCP server belongs to an organization, you need to first add glama.json to the root of your repository.
{
"$schema": "https://glama.ai/mcp/schemas/server.json",
"maintainers": [
"your-github-username"
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Please follow the instructions in the GitHub documentation.
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If the license does not appear on the server after some time, you can manually trigger a new scan using the MCP server admin interface.
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To manually sync the server, click the "Sync Server" button in the MCP server admin interface.
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.