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mcp server

noisefloor — is this number real?

Is this number real, or is it noise? Peek-safe A/B tests, change detection, honest forecasts.

Description as published by the maintainer. Source

  • version 0.2.0
  • active

active — Most recent push to the repository was 2026-08-02.

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 0 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 2026-08-02 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 0.2.0 Latest version string the maintainer published to the registry. as of fetch Model Context Protocol
Registry record last updated 2026-08-02 When the registry record was last updated by its maintainer. point in time Model Context Protocol
License MIT Licence GitHub detected in the repository. Detection can be wrong; the LICENSE file is authoritative. as of fetch GitHub
First listed in the MCP Registry 2026-08-02 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

Where to get it

Related, by what their authors tagged them

  • Grounded Reasoning — last commit 2026-07-06, shares conformal-prediction
    Verify multi-hop relational claims before an agent asserts them — zero tokens, with proof paths.
  • Distil — last commit 2026-08-08, shares conformal-prediction
    Reversibly compress tool outputs to recoverable handles; expand to exact original bytes on demand.
  • io.github.ChanMeng666/archlang-mcp — last commit 2026-08-06, shares zero-dependency
    Compile, describe, lint, validate, score and repair multi-storey and curved ArchLang floor plans.
  • io.github.DanceNitra/inspeximus — last commit 2026-08-06, shares zero-dependency
    Self-correcting agent memory + MCP server: recall, supersede/revert/review corrections, erasure.
  • io.github.DanceNitra/mnemo — last commit 2026-08-06, shares zero-dependency
    Self-correcting agent memory + MCP server: recall, supersede/revert/review corrections, erasure.
  • ai.mcpanalytics/analytics — last commit 2026-08-02, shares statistics
    The statistical analyst in your AI chat — validated, citable, re-runnable analysis of your data.
  • Statistics Canada MCP Server — last commit 2026-08-02, shares statistics
    Access Statistics Canada data via the Web Data Services API
  • io.github.ashwinvis/scb-opendata-mcp — last commit 2026-03-24, shares statistics
    Statistics Sweden’s open data made available as an MCP server, using Python and FastMCP
  • io.github.asokore/statcite — last commit 2026-08-05, shares statistics
    Official economic statistics with citations: World Bank, IMF WEO, ECB. Verify claimed figures.
  • io.github.cyanheads/eurostat-mcp-server — last commit 2026-08-04, shares statistics
    Search and query the Eurostat catalogue — EU economy, demography, trade, and NUTS regional data.

These share tags the maintainers applied themselves, such as conformal-prediction, zero-dependency, statistics. 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.

Also from beepboop2025

How the author describes it

Topics the maintainer set on GitHub: ab-testing, anytime-valid, change-detection, conformal-prediction, experimentation, forecasting, mcp, mcp-server, monitoring, python, sequential-testing, statistics, zero-dependency.

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Sources

  1. beepboop2025/noisefloor on GitHub — GitHub, observed , trust tier 3.
  2. Official MCP Registry — Model Context Protocol, observed , trust tier 1.