Agentery pricing intelligence · Provider profile · Entropy
Provider profile · independently tracked by Agentery
Entropy
Verifiable randomness for AI agents. Four tools, no auth, free forever. Agents make probabilistic decisions constantly: which provider to try, which sample to…
Agentery price verdictNo pricing observed
Billing model—
Last checked—pricing & liveness
What it does
The specific capability behind this listing, and where to get it.
Verifiable randomness for AI agents. Four tools, no auth, free forever. Agents make probabilistic decisions constantly: which provider to try, which sample to draw, which "arm to pull". Almost none of it is auditable. Entropy-MCP makes randomness defensible: correct draws, cryptographic proof they weren't rigged, statistical testing of any entropy source, and reproducible bandit selection. Tools: 1. random — correct draws, optionally reproducible Six operations: bytes, int, shuffle, choose, sample, constrained. The implementations are the point. Integers use rejection sampling, not modulo: random_byte % 10 silently over-represents small numbers, and this doesn't. Shuffles are Fisher-Yates and return a full permutation array so the result is auditable. Weighted selection without replacement uses Efraimidis-Spirakis, which is the method that doesn't distort probabilities. sample draws from six named distributions (uniform, normal, lognormal, exponential, triangular, beta) with a sum
MCPAWSMCPautonomy: infrastructure
Official Entropy links
Price status · observed daily
No public commercial pricing observed.
No price does not imply the product is free. Any code-host platform pricing is excluded.
Is Entropy good value?
Price is straightforward; the useful comparison is capability, compatibility and operational cost.
No price benchmark
No public commercial pricing observed.
Agentery has not observed a public price for this provider. No price does not mean free.
Observed commercial pricenone
Niche—
Price benchmarknot applicable
What to compare instead
Check capability before deciding
Compare capability, compatibility and operational cost against comparable providers — Agentery keeps the price status explicit and never invents a verdict.
Entropy's local market
Nearest products by what they do.
Z
zerobeaconmcp
—strong match · price unavailable
View profile →
A
agentspecframework
—strong match · price unavailable
View profile →
C
cronozen_proofmcp
$96/moobserved monthly
View profile →
L—
Lemma — Verifiable Provenance for AI Agentsmcp
$350/moobserved monthly
View profile →
R
random_mcpmcp
—strong match · price unavailable
View profile →
PM
Psychometrics MCPmcp
—strong match · price unavailable
View profile →
See the MCP response behind this page · get_agent_profile()
See the MCP response behind this pageget_agent_profile
{
"agent_id": "entropy",
"name": "Entropy",
"url": "https://smithery.ai/server/wolfendentheo/Entropy",
"logo": "https://agentery.com/logos/CP-B98YEQ.svg",
"niche": null,
"category": null,
"short_summary": "Verifiable randomness for AI agents. Four tools, no auth, free forever.\n\nAgents make probabilistic decisions constantly: which provider to try, which sample to…",
"task_performed": "Verifiable randomness for AI agents. Four tools, no auth, free forever.\n\nAgents make probabilistic decisions constantly: which provider to try, which sample to draw, which \"arm to pull\". Almost none of it is auditable. Entropy-MCP makes randomness defensible: correct draws, cryptographic proof they weren't rigged, statistical testing of any entropy source, and reproducible bandit selection.\n\nTools:\n\n1. random — correct draws, optionally reproducible\n\nSix operations: bytes, int, shuffle, choose, sample, constrained.\n\nThe implementations are the point. Integers use rejection sampling, not modulo: random_byte % 10 silently over-represents small numbers, and this doesn't. Shuffles are Fisher-Yates and return a full permutation array so the result is auditable. Weighted selection without replacement uses Efraimidis-Spirakis, which is the method that doesn't distort probabilities. sample draws from six named distributions (uniform, normal, lognormal, exponential, triangular, beta) with a sum",
"inputs_accepted": [],
"outputs_produced": [],
"integrations_available": [
"MCP",
"AWS"
],
"protocols_or_interfaces": [
"MCP"
],
"industry_fit": [
"general business"
],
"autonomy_level": "infrastructure",
"human_approval_needed": "unclear",
"pricing_model": "unclear",
"price": null,
"trust_or_rating_signal": [],
"evidence_quality": "low",
"entity_type": "infrastructure",
"regulated_data_suitability": "unclear",
"evidence_urls": [
"https://smithery.ai/server/wolfendentheo/Entropy"
],
"last_checked": "2026-09-12",
"how_to_connect": {
"website": "https://smithery.ai/server/wolfendentheo/Entropy",
"docs": null,
"mcp": null,
"a2a": null,
"api": null,
"protocols": [
"MCP"
],
"note": "Speaks MCP but publishes no endpoint we could verify — check the docs/website."
},
"liveness": {
"probed": false,
"alive": null,
"endpoint_kind": null,
"latency_ms": null,
"uptime_7d": null,
"checked_at": null,
"consecutive_failures": 0,
"status": "unknown"
},
"price_extras": {
"free_tier": null,
"unit_cost": null
},
"reported_success": null,
"feedback": "If you use this listing, call report_outcome afterwards — it sharpens rankings for everyone including you."
}