mcp-server-pronunciation

by JuhongPark

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool has a distinct purpose: check_mic for microphone setup, record for raw audio, practice for sentence drills, assess for detailed evaluation, converse for free-form conversation, quick_practice for random drills, retry for repeating, and suggest_sentence for generating sentences. No two tools overlap significantly in functionality.
Naming Consistency3/5
Naming conventions are mixed: some tools use single verbs (assess, converse, practice, record, retry), while others use verb_noun with underscores (check_mic, suggest_sentence) and one uses adjective_verb (quick_practice). This inconsistency reduces predictability, though the names are still clear.
Tool Count5/5
8 tools is a well-scoped number for a pronunciation practice server. It covers all essential workflows—microphone check, recording, assessment, practice, conversation, retry, and sentence suggestion—without being excessive or insufficient.
Completeness5/5
The tool set covers the full domain of pronunciation practice: checking audio input, recording, assessing with or without reference, free-form conversation, focused drills, random practice, retrying, and generating practice sentences. There are no obvious gaps for the stated purpose.
Average 4.5/5 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
- Last stable release on May 3, 2026
- No critical vulnerability alerts
- 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.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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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

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses that parameters have random defaults but does not discuss other behavioral aspects such as sentence generation source, repetition avoidance, or side effects.
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 well-structured with a concise purpose statement followed by Args and Returns sections, each providing essential information without redundancy.
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 no annotations and presence of output schema, the description covers purpose, parameters, and return value. However, it lacks details on how the sentence is generated (e.g., fixed set vs. dynamic) and any restrictions.
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?
Schema coverage is 0%, yet description compensates by listing allowed values for 'focus' and 'difficulty', and explaining default behavior (random selection). This adds significant meaning beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'suggest' and the resource 'a practice sentence', with explicit purpose of reading aloud. It is distinct from sibling tools like 'practice' or 'record' which handle execution or recording.
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 generating sentences but does not explicitly guide when to use this tool versus siblings like 'practice' or 'quick_practice'. No exclusion or alternative suggestions are given.
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 it lists devices and verifies access, returns a list. With no annotations, more detail (e.g., permissions required, read-only nature) would improve transparency, but the simplicity reduces gaps.
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?
Three sentences, front-loaded with purpose and usage guidance. Every sentence adds value; no fluff.
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?
Covers purpose and usage adequately for a zero-parameter tool with output schema. Could mention prerequisites like permissions, but not essential.
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?
No parameters exist, so baseline 4. No additional parameter info needed; description focuses on tool purpose.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists audio input devices and verifies microphone access, and mentions showing the default device. This distinguishes it from siblings like 'record' which records audio.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use this if the user reports recording problems', providing clear context for when to use. No explicit when-not-to or alternatives, but implied by sibling tool names.
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, description carries full burden. It discloses re-recording and re-assessing behavior and returns a report, but omits side effects, authentication needs, or rate limits. Adequate but not exhaustive.
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?
Concise, front-loaded with purpose, and uses clear Args/Returns structure. Every sentence adds value with zero waste.
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?
Description covers core behavior, parameter, and return value. Given output schema exists, return explanation suffices. Could expand on prerequisite of prior call, but overall adequate for a simple 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?
Schema has 0% description coverage, so description compensates by explaining 'duration' as 'Maximum recording duration in seconds (default 15, max 120),' adding meaning beyond type and default. No other parameters to clarify.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it retries the last practiced sentence by re-recording and re-assessing using the same reference text from a previous 'practice' or 'converse' call. This specific action distinguishes it from siblings like 'practice' and 'converse'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly notes 'Use this to let the user try again after getting feedback,' providing clear context for when to invoke. It implies a prior call exists but does not explicitly state prerequisites or when not to use.
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?
Since no annotations are provided, the description carries the full burden. It explains the tool picks a sentence based on criteria, records, and assesses. It notes that focus/difficulty are optional and duration defaults to 15 max 120. It could disclose more about side effects (e.g., saving recordings), but overall it's transparent.
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 concise and well-structured. The first sentence states the purpose, the second explains the combination, and the Args section lists parameters with options. No unnecessary words.
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?
The tool has three optional parameters and an output schema. The description covers the main behavior and return value. It could mention what happens with invalid inputs, but given the simple nature, it's fairly complete.
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%, but the description provides full explanations for all three parameters: focus options, difficulty options, and duration default and max. 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'picks a random practice sentence' and 'drills it immediately', using specific verbs and resource. It distinguishes from siblings like 'suggest_sentence' and 'practice' by combining both steps.
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 mentions the tool combines two steps, implying it's for when you want both suggestion and practice. However, it does not explicitly state when not to use it (e.g., if you want to select a sentence manually) or provide alternatives.
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?
Although no annotations exist, the description explains key behaviors: auto-stop on silence, duration limits (default 30, max 120), and the components of the return value. It does not mention privacy or authentication, but for a recording tool this is sufficient.
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 with a summary, auto-stop note, usage list, and parameter details. It is slightly verbose but every sentence serves a purpose; no fluff.
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 the presence of an output schema, the description adds value by explaining the return content (transcript, feedback, guidance) and usage context. It covers the tool's role among siblings adequately, though it could detail edge cases like long silences.
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?
With 0% schema description coverage, the description fully compensates by explaining both parameters: target_hint (optional, for specific sentences) and duration (default 30, max 120, auto-stop). This adds significant meaning beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool records user speech, transcribes it, and returns transcript plus English feedback. It distinguishes itself from the sibling 'practice' tool for focused drills, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly lists when to use this tool (voice chats, casual feedback) and when to use an alternative (use 'practice' for focused drills). This provides clear guidance on tool selection.
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. It discloses auto-stop recording behavior and returns a detailed assessment. However, it could elaborate on processing time or privacy aspects. Overall, sufficiently transparent.
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?
Description is concise with clear sections: purpose statement, usage contrast, auto-stop detail, then structured args/returns. Every sentence is useful with no fluff.
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?
Covers use case, parameters, return, and differentiation from siblings. Could hint at required microphone access, but output schema exists, making it complete enough for an agent to act.
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?
Description adds meaning to both parameters: reference_text is 'the sentence to read aloud', duration includes default and max values. Schema has 0% coverage, so description fully compensates.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool is for drill mode pronunciation assessment of a specific sentence, distinguishing it from free-form chat and sibling tools like 'converse'. The verb 'practice' directly conveys the purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (explicit practice of a particular sentence) and when not to (free-form chat). Names the alternative 'converse' for casual feedback, providing clear guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description is highly transparent, detailing algorithms (Needleman-Wunsch, wav2vec2 CTC), bias mitigation, phoneme feedback, learner profiles, and prosody notes. It fully discloses 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with bullet points, each providing unique information. It front-loads the main purpose and is appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema, the description adequately covers inputs and output format (markdown report). It is complete for agent invocation, covering optional parameters and behavior differences.
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?
The description adds significant meaning beyond the schema (which has 0% coverage). It explains reference_text as expected text and audio_path as optional WAV path defaulting to last recording, providing context and usage examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool assesses the last recording or a specific audio file without re-recording, using the verb 'assess' and resource 'audio'. It distinguishes from sibling tools like 'record' and 'practice' by focusing on evaluation rather than creation or interactive practice.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use reference_text (for alignment and phoneme feedback) and what happens without it (only transcript and prosody). However, it does not explicitly exclude usage scenarios or mention alternative tools like 'converse' or 'check_mic'.
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?
Discloses auto-stop on silence detection, duration as maximum, and raw WAV return. No annotations provided, so description carries full burden; it covers key behaviors but could mention if recording requires mic permissions.
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?
Concise, front-loaded with purpose, then auto-stop, duration clarification, usage guidance, and explicit args/returns. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Completes all needed context: purpose, behavior, parameter meaning, return type, and comparative guidance. Sufficient for a simple tool with output schema.
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 lacks parameter description (0% coverage). Description provides meaning: duration is max recording time in seconds, with default 10 and max 120, adding essential context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it records audio from the microphone, auto-stops on silence, and returns a WAV file. It distinguishes from siblings 'converse' and 'practice' by noting they also analyze.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly advises preferring 'converse' or 'practice' for combined recording and analysis, using 'record' only for raw WAV. Also explains duration as max time not requiring full wait.
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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