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8 clients · secrets stay placeholders

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{
  "mcpServers": {
    "databutler-stats": {
      "type": "http",
      "url": "https://databutler.dev/api/mcp/stats"
    }
  }
}

claude mcp add --transport http databutler-stats https://databutler.dev/api/mcp/stats

[mcp_servers.databutler-stats]
url = "https://databutler.dev/api/mcp/stats"

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "databutler-stats": {
      "type": "remote",
      "url": "https://databutler.dev/api/mcp/stats",
      "enabled": true
    }
  }
}

{
  "mcpServers": {
    "databutler-stats": {
      "type": "http",
      "url": "https://databutler.dev/api/mcp/stats"
    }
  },
  "deeplink": "cursor://anysphere.cursor-deeplink/mcp/install?name=databutler-stats&config=eyJ0eXBlIjoiaHR0cCIsInVybCI6Imh0dHBzOi8vZGF0YWJ1dGxlci5kZXYvYXBpL21jcC9zdGF0cyJ9"
}

{
  "servers": {
    "databutler-stats": {
      "type": "http",
      "url": "https://databutler.dev/api/mcp/stats"
    }
  }
}

{
  "mcpServers": {
    "databutler-stats": {
      "httpUrl": "https://databutler.dev/api/mcp/stats"
    }
  }
}

extensions:
  "databutler-stats":
    enabled: true
    name: "databutler-stats"
    type: streamable_http
    uri: "https://databutler.dev/api/mcp/stats"
    timeout: 300

Quality 86 / 100good

protocol75 · weight 25

warn
protocol.modernnewest supported version is 2025-11-25; 2026-07-28 not supported, older versions are deprecated until 2027-07-28
n/a
protocol.statelessonly applies to 2026-07-28 servers
pass
protocol.transportstreamable HTTP
n/a
protocol.list_ttlonly applies to 2026-07-28 servers

authorizationn/a · weight 15

n/a
auth.prm, auth.as_metadata, auth.cimdno remote uses OAuth
n/a
auth.secret_in_urlno templated URL

tool hygiene100 · weight 30

pass
tools.descriptionsevery tool has a description
pass
tools.description_lengthdescriptions are concise
pass
tools.schemasevery tool has an object input schema
pass
tools.annotations6 of 6 tools declare readOnlyHint or destructiveHint
pass
tools.directory_hintsevery tool declares readOnlyHint, destructiveHint, idempotentHint and openWorldHint
pass
tools.token_costabout 918 tokens to load every tool
pass
tools.api_dumptools are not a one-to-one API dump

stability75 · weight 15

warn
stability.changes6 tool changes in 30 days
pass
stability.rug_pullno tool changed its meaning under the same name

dependenciesn/a · weight 15

n/a
deps.known_vulns, deps.mcp_sdk_version, deps.resolvableno npm or PyPI package

6 tools, about 918 tokens to load them all · tool set c15d2c7ad6cc · tools last changed 2026-10-03 · checked 2026-10-20 06:49 UTC

Tool changes

2026-10-03linear_regressionchangedtitle, annotations
2026-10-03bayes_updatechangedtitle, annotations
2026-10-03confidence_intervalchangedtitle, annotations
2026-10-03hypothesis_testchangedtitle, annotations
2026-10-03distributionchangedtitle, annotations
2026-10-03descriptive_statschangedtitle, annotations

Full history: list_changes · trend: quality JSON.

Checks run on what our credential-free, read-only probes observe; tools are never called and no code audit is performed. How it is computed.

Trust 90 / 100

duplicate-repo

provenance90

liveness100

freshness85

hygiene80

+repository +namespace-matches-repo +website +reachable +uptime-100% ~updated-50d-ago -duplicate-repo(16 names)

Derived from observable signals (official registry feed and our own credential-free probes); no code audit performed. How it is computed.

Endpoints

remote	auth	reachable	uptime 30d	p50	protocol	last ok
`https://databutler.dev/api/mcp/stats` streamable-http	none	yes	100%	217 ms	2025-11-25	2026-10-20

Tools (6)

`bayes_update`read-only	Discrete Bayesian update: given competing hypotheses each with a prior and the likelihood of the observed evidence, return normalised posteriors. Priors are renormalised to sum to 1.
`confidence_interval`read-only	Confidence interval for a mean (t-based; from data, or n/mean/sd) or a proportion (Wilson; successes/n). kind = mean \| proportion; confidence default 0.95.
`descriptive_stats`read-only	Summary statistics for a numeric array: mean, median, sd, variance, quartiles, IQR, skewness, min/max.
`distribution`read-only	Evaluate a probability distribution (normal, t, chi2, binomial, poisson): pdf/pmf and cdf at a value, and/or the quantile at a probability, plus mean & variance. Params per dist: normal {mean,sd}, t {df}, chi2 {df}, binomial {n,p}, poisson {lambda}.
`hypothesis_test`read-only	Run a significance test and get the statistic, p-value, and a plain-language interpretation with assumptions. test = one-sample-t {data, mu0}, two-sample-t {data1, data2}, one-proportion-z {successes, n, p0}, two-proportion-z {successes1,n1,successes2,n2}, chi2-gof {observed, expected?}, chi2-independence {table}. Optional tail: two-sided (default) \| greater \| less; alpha default 0.05.
`linear_regression`read-only	Simple linear regression of y on x: slope, intercept, r, r², slope std error and p-value, equation.

Schemas: list_tools.

Also listed as

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Official server.json

{
  "name": "io.github.physics-star-cat/databutler-stats",
  "$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
  "remotes": [
    {
      "url": "https://databutler.dev/api/mcp/stats",
      "type": "streamable-http"
    }
  ],
  "version": "1.0.0",
  "repository": {
    "url": "https://github.com/physics-star-cat/databutler",
    "source": "github"
  },
  "websiteUrl": "https://databutler.dev/api",
  "description": "Exact statistics & probability: distributions, hypothesis tests, CIs, Bayesian updates, regression."
}