voice-quality-api
Server Details
Measure voice/VoIP path quality -> estimated MOS + live network metrics
- Status
- Unhealthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- Gomess8/API
- GitHub Stars
- 0
- Server Listing
- Voice Quality API
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Tool Definition Quality
Average 4.2/5 across 1 of 1 tools scored.
Only one tool exists, so there is no ambiguity. The tool has a clear and distinct purpose.
The single tool name 'measure_voice_quality' follows a clear verb_noun pattern, consistent and descriptive.
A single tool for a dedicated API can be appropriate, but it is on the lower end of the ideal range (3-15). The server could benefit from additional tools like historical analysis or multiple destination testing.
The tool covers its stated purpose well—measuring voice quality with MOS and network metrics. Minor gaps like batch testing or quality thresholds are missing but not critical for the core functionality.
Available Tools
1 toolmeasure_voice_qualityMeasure voice qualityAInspect
Measure the quality of a voice/VoIP path to a destination and return the estimated MOS (ITU-T G.107 E-model) plus live network metrics (RTT, jitter, packet loss). Useful before routing or starting a voice-agent call. The MOS is an objective estimate, not a perceptual measurement.
| Name | Required | Description | Default |
|---|---|---|---|
| from | No | Optional probe location selectors, e.g. ['eu-west','us-east'] | |
| codec | No | Narrowband codec to model | G711 |
| target | Yes | IP, host, or media endpoint to measure toward |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that MOS is an objective estimate (not perceptual) and that live metrics (RTT, jitter, packet loss) are returned. With no annotations, this adds meaningful behavioral context beyond the input schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, zero waste. Front-loaded with action and output, followed by usage context and a clarifying caveat. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, usage context, output metrics, and a behavioral caveat. Without an output schema, the description adequately hints at return values, though a slightly more explicit output structure would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All three parameters are fully described in the input schema (100% coverage). The description adds no additional semantic nuance for the parameters, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Explicitly states it measures voice/VoIP path quality and returns MOS plus network metrics. Verb 'measure' with specific resource and outputs, distinguishing it conceptually from other possible tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear usage guidance: 'Useful before routing or starting a voice-agent call.' However, it does not include when-not-to-use or alternative tool references, though no siblings exist.
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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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
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The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
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Credentials required to access the server are missing or invalid
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