A
license-
qualityB
maintenanceEnables checking real-time operational status of 75+ AI services (OpenAI, Anthropic, Cursor, etc.) through tools like check_ai_status and list_ai_services.
MIT
llm-latency-tracker
Server Details
Measured latency & uptime for AI inference APIs, by region. Exposes a get_ai_api_latency tool.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- mazamaka/llm-latency-tracker
- GitHub Stars
- 1
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Tool Definition Quality
A4.1/5.0
Tool DescriptionsA
Average 4.1/5 across 1 of 1 tools scored.
Server CoherenceA
Disambiguation5/5
With only one tool, there is no risk of confusion between tools. The single tool has a clear and distinct purpose.
Naming Consistency5/5
The single tool name follows a consistent verb_noun pattern (get_ai_api_latency) and is self-explanatory.
Tool Count3/5
One tool feels thin for a tracker that could benefit from separate tools for different queries (e.g., by region or provider). However, it may be sufficient for the stated purpose.
Completeness3/5
The tool provides latency and uptime data, but lacks filtering or granular options. The surface is minimal and may not cover all user needs.
Available Tools
1 toolget_ai_api_latencyAInspect
Measured latency (TTFB p50/p95) and uptime rankings of AI inference API providers by region, from llmlatency.dev.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| region | No | eu-hetzner, us-central, ap-tokyo or sa-east; omit for all |
Tool Definition Quality
A4.1/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the full burden and explicitly states the data is measured and sourced, implying a read-only operation. It does not mention side effects, which is fine for a data retrieval tool.
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, clear sentence that conveys all necessary information without waste.
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 simplicity (one optional parameter, no output schema), the description fully explains what the tool returns and the data source, making it complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the single parameter 'region' is well described in the schema. The description does not add additional parameter semantics, so baseline 3 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 provides measured latency (TTFB p50/p95) and uptime rankings for AI inference API providers, sourced from llmlatency.dev, with optional region filtering. This is specific and informative.
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 retrieving latency and uptime data, but does not provide explicit guidance on 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.
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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:
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