macwhisper-mcp-server

by docdyhr

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Server Quality Checklist

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Latest release: v1.2.0
Disambiguation4/5
Each tool has a distinct role: transcription, cancellation, model listing, path listing, and watch lifecycle. The only slight overlap is between transcribe_audio and get_watch_results, both returning transcripts, but they serve different workflows (direct vs. watched).
Naming Consistency5/5
All tools follow a consistent snake_case verb_noun pattern (e.g., transcribe_audio, start_watch), making the API predictable and easy to navigate.
Tool Count5/5
Seven tools is well within the ideal range; each tool addresses a specific need without redundancy.
Completeness4/5
The core transcription workflow is covered (transcribe, cancel, list models, list paths), and the watch folder feature adds a complete sub-workflow. Minor gap: no way to retrieve a past transcription result outside of the watch queue, but not essential for the main purpose.
Average 4.2/5 across 7 of 7 tools scored. Lowest: 3.5/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 21 commits in the last 12 weeks
- Last stable release on August 13, 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.
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{
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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?
With no annotations, the description must convey behavioral traits, but it only states the basic action. It omits important details such as side effects (e.g., whether watched files are released), error conditions, or required 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?
The description is a single, complete sentence with no unnecessary words. It is front-loaded and efficient.
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?
While the tool is simple (zero parameters), the description does not mention the output or any side effects, despite an output schema being present. It is minimally adequate but leaves some context uncovered.
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 tool has zero parameters, so the description does not need to add parameter meaning. The schema already covers all 0 parameters, meeting the baseline for high schema coverage.
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 action ('Stop') and the resource ('the active folder watcher'), making the purpose unambiguous. It effectively distinguishes from siblings such as 'start_watch'.
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 (e.g., 'cancel_transcription' or 'start_watch'). It lacks context on prerequisites or expected state.
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, the description fails to disclose behavioral traits like authentication needs or side effects, providing minimal transparency for a read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no unnecessary words, front-loaded with the verb and resource.
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 is simple with no parameters and an output schema, so the description is nearly complete; however, it could mention that it returns a list of paths.
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 no parameters, so the description adds no param info; but with 100% schema coverage and zero parameters, a baseline score of 4 is appropriate.
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 returns directories the server is allowed to read audio from, with a specific verb and resource, distinguishing it from siblings like transcribe_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 verifying allowed paths before audio operations, but lacks explicit when-to-use or alternatives, making it adequate but not fully guided.
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 provided, and the description does not disclose behavior when no transcription is running (e.g., error vs no-op). Without this, the agent lacks full understanding of edge cases.
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?
Single sentence, no wasted words. Description is appropriately sized and front-loaded with the action.
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 parameters and an output schema (not shown), the description is minimal. It fails to specify the effect when no transcription exists, but with output schema, return values may be documented elsewhere. Adequate but not thorough.
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 schema coverage is 100%. Per guidelines, 0 parameters yields baseline 4. Description adds no additional parameter info, which is fine.
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 cancels the currently running transcription, which is a specific verb+resource. It distinguishes from siblings like transcribe_audio (starts) and stop_watch (stops watch, not transcription).
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?
Implies use when a transcription is running, but does not explicitly state when not to use or what happens if none is running. However, the context is clear enough for a simple action.
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 discloses the important behavioral trait of clearing the queue after returning results, and lists the fields in each entry. It does not mention idempotency or behavior when queue is empty.
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?
Two sentences, front-loaded main action, no extraneous information. Every sentence earns its place.
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 provides helpful detail about return fields. However, it lacks information about pagination or behavior when no results exist.
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?
There are no parameters, so schema coverage is 100%. The description adds no parameter info, which is appropriate. Baseline score for zero parameters is 4.
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 returns completed watch-folder transcriptions and clears the queue, distinguishing it from sibling tools like 'start_watch' and 'transcribe_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 after starting a watch and after transcriptions complete, but does not explicitly state when to use this tool versus alternatives 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?
With no annotations provided, the description carries the burden of disclosing behavior. It reveals the output format for both MacWhisper and whisper-cpp entries, the conditional presence of whisper-cpp models based on an environment variable, and the requirement that the CLI be reachable. This is substantial behavioral disclosure, though it doesn't cover error scenarios or exact return structure beyond the string formats.
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 front-loaded with the purpose and then provides necessary formatting details in a structured way. Each sentence adds value for the consumer, though the second and third sentences are somewhat dense. It is not overly verbose for the information it conveys.
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 (not shown), the description explains the semantic meaning of the output strings (active marker, engine prefixes) and how to feed them into transcribe_audio. It also covers prerequisites and conditional behavior, making it complete for a list tool with no params.
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 tool has zero parameters, so the input schema is empty and schema coverage is 100%. The description correctly adds no parameter-specific details. Per the rubric, 0 params warrants a baseline of 4, and there is nothing to add beyond that.
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 opening sentence 'Return the transcription models available across all engines' uses a specific verb ('Return') and resource ('transcription models') with a clear scope. This clearly distinguishes it from sibling tools like transcribe_audio or start_watch, which perform different actions.
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 and how to use the tool: it lists models formatted for use with transcribe_audio, and it notes the prerequisite that the MacWhisper CLI must be reachable even for whisper-cpp. It does not explicitly name alternatives or exclusions, but the context is clear enough for selecting this tool.
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 are provided, so the description carries the full transparency burden. It discloses the access restriction (must be inside allowed path), the unavailability of chat uploads, and the recommended behavior on access-denied errors. However, it does not explicitly mention potential side effects like whether persist=True saves to history (covered in schema) or whether the transcription is fully local. It adds substantial context beyond the schema but still has some 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?
The description is structurally efficient: a one-sentence purpose, an IMPORTANT constraint block, and a concise error-handling paragraph. Each sentence adds value with no redundancy, and the critical warnings are front-loaded for quick scanning.
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 tool's complexity (5 parameters, engine alternatives, language defaults) and the presence of an output schema (so return format is documented), the description covers the essential usage context: local file requirement, chat uploads inaccessible, and error handling. It does not explicitly mention when to prefer start_watch for continuous/batch transcription, but the description remains sufficiently complete for an agent to use the tool correctly.
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 100% parameter coverage with detailed descriptions for all 5 parameters, so the baseline is 3. The description adds important semantics for the path parameter: it must be on the Mac filesystem in the allow-list, and chat uploads are not accessible. This is not fully captured in the schema's path description, making the overall parameter understanding richer.
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 opens with a precise verb and resource: 'Transcribe a local audio file and return the transcript.' This clearly identifies the tool's purpose and distinguishes it from sibling tools such as cancel_transcription, list_models, and start_watch, which are support operations rather than the core transcription action.
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 states when to use the tool: for local files inside the allow-list, and it excludes chat uploads. It also provides specific error-handling guidance: if access-denied, do not attempt alternatives (downloading models, external APIs, in-process speech recognition); instead ask the user to save the file locally and retry. This is clear when-to-use and when-not-to-use 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It explains that files are automatically transcribed and moved to a 'done' directory, mentions the env var override, and states the allow-list requirement with rejection behavior. It also points to a sibling for results, giving a comprehensive view of the tool's side effects and constraints.
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 tightly structured with a one-line purpose, followed by two sentences of essential operational details and a pointer to the results tool. Every sentence contributes unique information without redundancy or filler.
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's moderate complexity (background watch, side effects, allow-list constraint) and the presence of an output schema, the description covers all necessary aspects: what it does, how it behaves, what constraints apply, and how to retrieve results. It equips an agent to decide when and how to use it effectively.
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 already describes the 'folder' parameter as an absolute or ~-prefixed path. The description adds meaningful context: it is the incoming directory for watched files, and both this directory and the derived done directory must be inside the allow-list. This goes beyond the schema by clarifying parameter role and constraints.
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 opens with 'Start watching a folder for new audio files to auto-transcribe,' which is a specific verb-object phrase that clearly states the tool's function. It is easily distinguishable from sibling tools like transcribe_audio, stop_watch, and get_watch_results, which involve different actions.
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 clearly implies when to use this tool: when you want automatic transcription of newly dropped files. It also guides the user to call get_watch_results() to retrieve transcriptions. However, it does not explicitly contrast this with transcribe_audio for one-off transcription, so the exclusion guidance is not fully spelled out.
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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