noisefloor — is this number real?
PYPI · NOISEFLOOR · SCANNED SEP 20
Is this number real, or is it noise? Peek-safe A/B tests, change detection, honest forecasts.
Available components
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →
Supply Chain Security50
- Malware scan not yet available for this package.Unverified
- No known CVEs affecting this package version or its production dependencies.Pass
- Runs hatchling.build at install time, a recognised native-build step with no shell scripting around it. View diagnostics → Pass
- No production dependencies, so there is no dependency health to assess. View diagnostics → Pass
Provenance & Transparency45
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- Clear OSI-approved license (MIT).Pass
- Actively maintained (last published 49 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability84
- 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).Pass
- AI-judged instruction clarity (excellent).Pass
- Context-footprint check failed: tool/resource definitions use about 827 tokens (~137/item across 6 items; 6 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management93
- Stability observed for 28 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage96
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 89% of tool parameters carry a description.Partial
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 6 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 7 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities60
- Spec-recency check failed: implements MCP spec 2025-06-18; the latest is 2026-07-28. See how to fix → Fail
How do I install the noisefloor — is this number real? MCP server?
noisefloor — is this number real? runs locally as a PyPI package, launched with uvx noisefloor. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · noisefloor
claude mcp add beepboop2025-noisefloor -- uvx noisefloor
{
"mcpServers": {
"beepboop2025-noisefloor": {
"command": "uvx",
"args": [
"noisefloor"
]
}
}
} {
"servers": {
"beepboop2025-noisefloor": {
"command": "uvx",
"args": [
"noisefloor"
]
}
}
} codex mcp add beepboop2025-noisefloor -- uvx noisefloor
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"beepboop2025-noisefloor": {
"type": "local",
"command": [
"uvx",
"noisefloor"
],
"enabled": true
}
}
} openclaw mcp add beepboop2025-noisefloor --command uvx --arg noisefloor
mcp_servers:
beepboop2025-noisefloor:
command: "uvx"
args: ["noisefloor"] {
"McpServers": {
"beepboop2025-noisefloor": {
"Transport": "stdio",
"Command": "uvx",
"Arguments": [
"noisefloor"
]
}
}
} assistant mcp add beepboop2025-noisefloor -t stdio -c uvx -a noisefloor
{
"mcpServers": {
"beepboop2025-noisefloor": {
"command": "uvx",
"args": [
"noisefloor"
]
}
}
} Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 19 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 87 to 90. That category is still filling its 30-day observation window: 26 days of observed history at the previous scan, 27 at this one. The score rises as the window fills, whether or not the server changes.
- 17 Sept 26 −14
- Malware scan: pass → unverified ▼ security
- 16 Sept 26 +12
- Malware scan: unverified → pass ▲ security
- Security disclosure: unverified → fail ▼ functional
- Stability: pass → 0.80 functional
- 15 Sept 26 0
- Stability: 0.97 → pass security
- Security disclosure: fail → unverified ▼ functional
- 14 Sept 26 −14
- Malware scan: pass → unverified ▼ security
- 12 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 87 to 90. That category is still filling its 30-day observation window: 26 days of observed history at the previous scan, 27 at this one. The score rises as the window fills, whether or not the server changes.
- 11 Sept 26 +15
- Malware scan: unverified → pass ▲ security
- 10 Sept 26 −14
- Malware scan: pass → unverified ▼ security
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 20 Sept 2026 · Analysed pypi/noisefloor@0.2.0
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | pypi |
Background: How many MCP packages publish verified provenance →
Install scripts 1 script
| Hook | Tier | Command |
|---|---|---|
| build_backend | allowlisted | hatchling.build |
Background: Why install scripts are a supply-chain risk →
Dependencies 0 packages
| Packages resolved | 0 |
|---|---|
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
ab_test Peek-safe A/B verdict ~140
Can you call a winner on an A/B test yet? Uses anytime-valid confidence sequences, so it is SAFE TO RUN AFTER EVERY OBSERVATION — peeking does not inflate the false-positive rate the way a t-test or z-test does.
| Name | Type | Req | Description |
|---|---|---|---|
| a_label | string | – | – |
| a_successes | integer | yes | conversions in arm A |
| a_total | integer | yes | total observations in arm A |
| alpha | number | – | error budget, default 0.05 |
| b_label | string | – | – |
| b_successes | integer | yes | conversions in arm B |
| b_total | integer | yes | total observations in arm B |
No output schema declared.
No examples provided.
did_it_change Did this metric really change? ~103
Did a metric actually change, or is the move noise? Detects both rises AND collapses against the metric's own history, with a stated false-alarm rate and no assumption about the distribution.
| Name | Type | Req | Description |
|---|---|---|---|
| half_life | number | – | optional: readings after which old history counts half, for drifting metrics |
| two_sided | boolean | – | detect drops as well as rises (default true) |
| values | array | yes | the metric's history, oldest first |
No output schema declared.
No examples provided.
forecast_next Calibrated next-value forecast ~67
What should the next reading be, and within what range? Range adapts to the metric's recent volatility and stays valid even when the metric shifts.
| Name | Type | Req | Description |
|---|---|---|---|
| nominal | number | – | range coverage, default 0.8 |
| values | array | yes | the metric's history, oldest first |
No output schema declared.
No examples provided.
real_or_sampling Real effect, or sampling noise? ~93
Did the metric move, or did the sample size underneath it move? Run this before reporting any RATE as a change — conversion rates, error rates and click-through all shift when the denominator shifts, for reasons that have nothing to do with the thing being measured.
| Name | Type | Req | Description |
|---|---|---|---|
| sample_sizes | array | yes | the denominator behind each reading, same order and length |
| values | array | yes | the metric's history, oldest first |
No output schema declared.
No examples provided.
score_forecasts Score past forecasts honestly ~76
How good would these forecasts actually have been? Grades every prediction the tool would have made over the history, using only what was known at the time, and reports calibration plus the worst misses.
| Name | Type | Req | Description |
|---|---|---|---|
| nominal | number | – | range coverage, default 0.8 |
| values | array | yes | the metric's history, oldest first |
No output schema declared.
No examples provided.
which_metrics_matter Rank metrics by real signal ~102
You watch many metrics; which genuinely stand out? Controls the false discovery rate across all of them at once, which per-metric thresholds do not: forty metrics each alerting wrongly 5% of the time means two false alarms every round.
| Name | Type | Req | Description |
|---|---|---|---|
| alpha | number | – | false-discovery rate, default 0.1 |
| evidence | object | yes | metric name -> evidence value, e.g. the 'evidence' field from did_it_change |
No output schema declared.
No examples provided.
What is the noisefloor — is this number real? MCP server?
noisefloor — is this number real? is an MCP server listed in the public MCP registry as io.github.beepboop2025/noisefloor. Is this number real, or is it noise? Peek-safe A/B tests, change detection, honest forecasts. This page covers its PyPI package (noisefloor).
Is the noisefloor — is this number real? MCP server safe to use?
noisefloor — is this number real? scores 68 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 20 September 2026. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the noisefloor — is this number real? MCP server expose?
noisefloor — is this number real? exposes 6 tools: ab_test, did_it_change, forecast_next, real_or_sampling, score_forecasts, which_metrics_matter. Their descriptions and schemas cost roughly 581 tokens of context every time the server is loaded.
Is the noisefloor — is this number real? MCP server still maintained?
noisefloor — is this number real? is still listed as active in the MCP registry. We last reached this channel on 20 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.
What licence is the noisefloor — is this number real? MCP server under?
noisefloor — is this number real? declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.