Blabber-MCP
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool has a clearly distinct purpose of converting text to speech, and no other tools exist to cause confusion.
Naming Consistency5/5The single tool name 'text_to_speech' follows a clear verb_noun pattern (text_to_speech), and with only one tool, consistency is inherently perfect as there are no other names to compare against.
Tool Count2/5A single tool is too few for most server purposes, as it severely limits functionality and scope. While the tool itself is well-defined, the server lacks breadth, making it feel thin and under-scoped for typical MCP use cases.
Completeness2/5The server is severely incomplete for a text-to-speech domain. It only provides conversion to speech, with no tools for managing audio files (e.g., list, delete, play controls), voice selection beyond the default, or other related operations like speech-to-text, leading to significant gaps in coverage.
Average 3.5/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- 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.
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This repository includes a glama.json configuration file.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that audio is saved to a file and optionally played, which covers some output behavior, but lacks details on file location, naming, permissions, error handling, rate limits, or authentication needs. For a tool with no annotations, this leaves significant gaps in understanding its operational traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that efficiently conveys the core functionality, default settings, and optional features without any wasted words. It's front-loaded with the primary purpose and includes all necessary details concisely.
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?
Given the complexity (5 parameters, no output schema, no annotations), the description is adequate but incomplete. It covers the basic purpose and some behavioral aspects (saving and playing), but lacks details on output format, error handling, and other operational context that would be helpful for an agent to use it effectively without annotations.
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%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema by mentioning the default voice (alloy) and the optional play feature, but doesn't provide additional syntax, format, or usage context for parameters. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Converts text into spoken audio'), identifies the resource ('using OpenAI TTS'), and provides implementation details ('saves it to a file, and optionally plays it'). It distinguishes itself by mentioning the default voice (alloy) and the optional play feature, which would be relevant if there were 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 Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage through the phrase 'optionally plays it,' suggesting when the play parameter might be used, but provides no explicit guidance on when to use this tool versus alternatives (though none are listed as siblings). There's no mention of prerequisites, limitations, or specific scenarios for choosing different models or voices.
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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- 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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