gaudio-developers-mcp
OfficialServer Quality Checklist
- Disambiguation4/5
Tools are mostly distinct with clear purposes, though there is intentional overlap between granular workflow tools (upload_file/create_job/get_job) and high-level 'all-in-one' wrappers (separate_audio, sync_lyrics). Descriptions mitigate confusion by explicitly labeling the latter as all-in-one and specifying when to use each path.
Naming Consistency5/5All tools follow a consistent gaudio_verb_noun pattern using snake_case. Verbs (create, get, list, separate, sync, upload) and nouns (job, models, audio, lyrics, file) are applied uniformly throughout the set.
Tool Count5/5Seven tools is well-scoped for an audio processing API, providing granular primitives (upload, create, get) alongside convenience wrappers for common workflows (separation, lyrics sync), plus metadata tools (models, key info) without bloat.
Completeness4/5Covers the full job lifecycle (upload, create, get/status) for the three model categories mentioned (stem, dme, text_sync). Minor gaps exist for operational completeness (no list_jobs, cancel_job, or delete operations), but core CRUD and domain-specific workflows are present.
Average 4.1/5 across 7 of 7 tools scored. Lowest: 3.5/5.
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: v1.1.3
Tools from this server were used 2 times in the last 30 days.
This repository includes a glama.json configuration file.
- This server provides 7 tools. View schema
No known security issues or vulnerabilities reported.
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Tool Scores
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full disclosure burden. It compensates partially by listing the specific data fields returned, implicitly indicating this is a metadata retrieval operation. However, it lacks explicit safety assertions (read-only nature), rate limit warnings, or authentication requirements.
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 front-loaded with the action ('Get API key information') followed by a colon-delimited list of return fields. Every word provides value; no redundancy.
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?
For a zero-parameter information retrieval tool without output schema, the description adequately compensates by enumerating the expected return fields (credits, status, models, etc.). Sufficient for tool selection, though auth context could strengthen it.
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?
Input schema contains zero parameters, establishing a baseline score of 4 per rubric rules. No parameter description compensation is required.
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?
Description uses specific verb 'Get' with resource 'API key information' and enumerates the returned fields (description, creation date, credits, etc.). It implicitly clarifies that 'key' refers to API credentials rather than musical keys (relevant given audio-processing siblings), but does not explicitly differentiate from sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description provides no guidance on when to invoke this tool versus others, nor prerequisites like authentication state. It simply states what the tool retrieves without contextual usage advice.
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?
With no annotations provided, the description carries significant weight. It effectively documents the four status states and their meanings, notes that downloadUrl is conditionally present on success, and warns about the 48-hour URL expiration—critical behavioral constraints not visible in the schema.
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 sentences with zero waste: purpose statement first, followed by status enumeration, followed by expiration constraint. Every sentence delivers unique, high-value information without redundancy.
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?
Given the lack of output schema, the description adequately compensates by detailing the expected response structure (status values and downloadUrl behavior). Minor gaps remain regarding error handling (e.g., invalid jobId responses), but it is sufficiently complete for invocation.
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 description coverage is 100%, documenting both jobId (with origin references) and model. The description adds no additional parameter semantics beyond what the schema already provides, meeting the baseline expectation for high-coverage schemas.
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?
The description clearly states the core action ('Check job status and get results') with a specific verb and resource. While it implies retrieval from sibling creation tools via the schema's jobId description, the description text itself does not explicitly distinguish when to use this versus creating jobs, falling short of a 5.
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?
Usage is implied through the jobId parameter reference to sibling tools (gaudio_create_job, gaudio_separate_audio), and the status lifecycle description suggests a polling pattern. However, there are no explicit guidelines on when to call this tool, polling frequency, or terminal state handling.
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 the full disclosure burden. It adds valuable semantic context for the category values but omits safety characteristics (read-only status), return format details, and pagination behavior for the list operation.
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 with zero waste: the first identifies the operation, the second explains filter options. Information is front-loaded and every sentence earns its place.
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?
For a simple listing tool with one optional parameter and high schema coverage, the description adequately explains the filtering options. It could benefit from mentioning typical usage flow (discovering models before job creation) but covers the essential complexity.
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?
Despite 100% schema coverage (baseline 3), the description adds significant value by translating technical enum values ('stem', 'dme', 'text_sync') into domain concepts ('instrument separation', 'dialogue/music/effects', 'lyrics sync'), aiding the agent in selecting appropriate filters.
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?
The description clearly states the specific action ('List') and resource ('Gaudio AI models'), distinguishing it from sibling job-processing tools (gaudio_create_job, gaudio_separate_audio) by identifying this as a metadata discovery operation.
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?
The description explains what each category filter means (stem, dme, text_sync), providing implicit usage context, but lacks explicit guidance on when to call this tool relative to siblings (e.g., 'use before gaudio_create_job') or when not to use it.
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, so description carries full burden. Discloses async polling behavior ('poll until done'), 72-hour uploadId validity, and return of download URLs. Does not disclose error handling, cancellation behavior, or rate limits.
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?
Four dense sentences with zero waste. Front-loaded workflow diagram (arrows), followed by conditional parameter guidance and format support. Every clause earns its place.
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?
For an async polling tool with 5 parameters and no output schema, description adequately covers returns (download URLs) and lifecycle. Could improve by mentioning possible error states job statuses or timeout behavior.
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?
Schema coverage is 100% (baseline 3). Description adds significant domain context: file format support (WAV/MP4 etc. not in schema), Stem vs DME model semantics for 'type' parameter, and uploadId reuse workflow. Exceeds baseline meaningfully.
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 verb+resource (audio separation) and workflow (upload→job→poll→URLs). 'All-in-one' effectively distinguishes from granular siblings (gaudio_upload_file, gaudio_create_job, gaudio_get_job) without explicitly naming them, though explicit comparison would strengthen differentiation.
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 conditional logic: when to provide 'type' (Stem Separation) vs omit it (DME), and when to use uploadId vs filePath. Supported formats are listed. Lacks explicit 'use this instead of X' 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, so description carries full burden. It adds valuable conditional logic for parameter requirements, but lacks disclosure about operational behavior: async nature of jobs, need to poll status via gaudio_get_job, credit consumption, or error handling. Does not contradict any annotations.
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?
Highly efficient three-sentence structure. Front-loaded with core purpose ('Create a processing job'), followed by conditional parameter guidance, then sibling redirection. No wasted words; every clause provides actionable information.
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 parameter configuration, but given the presence of gaudio_get_job as a sibling and the async nature of job processing, the description should mention that created jobs are asynchronous and require status checking via the get_job tool. No output schema exists to compensate.
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?
Schema coverage is 100% (baseline 3). Description adds significant value by providing concrete model examples (gsep_music_hq_v1), explaining the conditional requirement logic for the 'type' parameter, and clarifying uploadId sourcing from gaudio_upload_file.
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 verb ('Create') + resource ('processing job') + input ('uploaded file'). Distinguishes from gaudio_sync_lyrics by explicitly redirecting text sync tasks there, and implies distinction from gaudio_upload_file by requiring an uploadId from that tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Excellent explicit guidance: states when 'type' parameter is required (Stem Separation models) vs not needed (DME models), provides concrete examples ('vocal', 'vocal,drum'), and explicitly names alternative tool 'gaudio_sync_lyrics' for text sync use cases.
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?
With no annotations provided, the description carries full behavioral disclosure burden. It successfully reveals: asynchronous polling nature, specific job type created (gts_lyrics_line_v1), return structure (CSV + JSON URLs), file constraints (UTF-8, 60 char limit), and size limits (1GB/10min). Could improve by mentioning failure modes or blocking behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely efficient: first sentence establishes entire workflow with arrow notation; second sentence packs all file and audio constraints. No redundancy. Every clause delivers novel information beyond schema.
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?
Excellent coverage for a 6-parameter async job tool lacking output schema. Compensates by detailing return format (CSV columns), input validation rules, and pipeline stages. Only minor gaps: missing duration estimates, retry behavior, or error handling specifics.
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?
Schema coverage is 100% with adequate individual parameter descriptions, establishing baseline 3. Description adds significant value by specifying file content requirements (.txt, UTF-8, min 2 lines, max 60 chars) and audio constraints (1GB/10min) not present in parameter descriptions, plus return value semantics.
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?
Description uses specific verb chain ('upload → create → poll → return') and identifies exact resource (lyrics sync) and output format (CSV with timestamp/lyric_text/confidence_score). 'All-in-one' clearly positions this as an end-to-end workflow distinct from sibling tools like gaudio_upload_file and gaudio_create_job.
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?
The 'All-in-one' framing implies this is a convenience wrapper for the complete pipeline, distinguishing it from siblings that handle individual steps (upload_file, create_job, get_job). However, it lacks explicit 'when not to use' guidance (e.g., if files are already uploaded or custom polling is needed).
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, so description carries full burden. Discloses multipart upload lifecycle (create→chunk→complete), return value semantics (uploadId, 72h validity), reusability pattern, and supported formats. Lacks explicit error handling or rate limit disclosure, but otherwise comprehensive.
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?
Four efficient sentences: purpose first, multipart mechanics second, return value lifecycle third, format constraints fourth. No repetition of schema structure or tautology. Information density is high with zero waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Compensates for missing output schema by documenting the key return value (uploadId) and its temporal validity (72h). Explains workflow integration with job-related siblings. Format coverage is comprehensive. No gaps given the tool's complexity.
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?
Schema has 100% coverage (filePath fully self-documenting), establishing baseline 3. Description adds critical semantic constraints—specifically the supported format list (WAV, FLAC, etc.)—which defines valid inputs for the filePath parameter beyond the schema's generic 'absolute path' description.
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 'Upload' with clear resource 'local audio/video/text file' and destination 'Gaudio servers'. Distinguishes from job management siblings (create_job, get_job) by being the file ingestion step, and explicitly notes the uploadId is used 'across multiple jobs' clarifying workflow relationship.
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 that the returned uploadId is reusable across multiple jobs, implicitly positioning this as a prerequisite step before job creation. Missing explicit 'when not to use' (e.g., for already-hosted files) or named alternatives, but the sibling relationship is clear.
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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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.
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