ZBS Index What actually exists in applied AI, with the source next to it

mcp server

llm-latency-tracker

Measured latency & uptime for AI inference APIs, by region. Exposes a get_ai_api_latency tool.

Description as published by the maintainer. Source

  • version 1.0.0
  • active

active — Most recent push to the repository was 2026-07-23.

What this server can do

1 function, named and described by the server itself. Parameter names are shown because they say more about what a function does than its name usually does.

get_ai_api_latency(region)
Measured latency (TTFB p50/p95) and uptime rankings of AI inference API providers by region, from llmlatency.dev.

Last successful function declaration observed on . Source: https://llmlatency.dev/mcp. We list what the server declared; we do not call any of these functions.

Endpoint status observed on . Source: https://llmlatency.dev/mcp.

Signals

These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.

Signal Value What it measures Window Observed Source
GitHub stars 1 Number of GitHub accounts that bookmarked this repository since it was created. It is a bookmark count, not installs, not active users and not quality. cumulative, all time GitHub
Last commit 2026-07-23 Date of the most recent push to any branch. This is the strongest cheap indicator of whether the project is still maintained. point in time GitHub
Open issues 0 Open issues plus open pull requests, as GitHub counts them together. A high number can mean an active project or an abandoned one. as of fetch GitHub
Latest published version 1.0.0 Latest version string the maintainer published to the registry. as of fetch Model Context Protocol
Registry record last updated 2026-07-23 When the registry record was last updated by its maintainer. point in time Model Context Protocol
First listed in the MCP Registry 2026-07-23 Date this server was first published to the official MCP Registry. Not a usage or quality measure. point in time Model Context Protocol
repository status active The repository exists on GitHub and is not archived. This says nothing about how recently it was worked on. as of fetch GitHub
mcp tools declared 1 tools Number of functions the server itself declared when asked to list them. This is what the server offers an agent, not a measure of how well any of them work. as of probe llmlatency.dev
mcp endpoint status ok The server listed 1 function when asked. as of probe llmlatency.dev

Where to get it

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  • cn.housingsentinel/housing-sentinel — last commit 2026-07-16, shares llms-txt
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These share tags the maintainers applied themselves, such as benchmark, observability, openai, llms-txt. Common tags like "mcp" or "ai" are ignored for this: agreeing with six hundred other projects is not a similarity.

This is not a recommendation and not a test result. It is a map of what the authors said their work is about.

How the author describes it

Topics the maintainer set on GitHub: ai, anthropic, benchmark, latency, llm, llms-txt, mcp, observability, openai, python.

This record as data

Every field on this page, with its source and observation date, is in the catalog JSON. Fetch the whole kind at once instead of parsing this HTML.

GET /api/v1/entries/mcp_server.json

Sources

  1. mazamaka/llm-latency-tracker on GitHub — GitHub, observed , trust tier 3.
  2. Tools declared by the MCP server at https://llmlatency.dev/mcp — llmlatency.dev, observed , trust tier 1.
  3. Official MCP Registry — Model Context Protocol, observed , trust tier 1.