waveguard scan

Find outliers and anomalies in structured data — ideal as a second step after pulling records from Google Sheets, Airtable, Supabase, Notion databases, HubSpot,

liveverifiedunknown~5s typical

mcpprobedwaveguard

$0.0020

per call

plus $0.001 platform fee per run

Open MCP server; Cracked bills routing only

Provider Upstream docs

$Set up https://cracked-ai-pearl.vercel.app/SKILL.md, then use Cracked to run mcp-com-emergentphysicslab-waveguard /waveguard_scan for me.

Input

Field	Type	Description
training*	array	2+ examples of NORMAL/expected data — the known-good baseline. Typically the bulk of rows
test*	array	1+ data points to check for anomalies — new entries, recent rows, or the subset you want v
sensitivity	number	Anomaly threshold multiplier (default: 2.0). Lower = more sensitive. Higher = less sensiti
encoder_type	string (json \| numeric \| text \| timeseries \| tabular \| image)	Data encoder type. Omit to auto-detect from data shape.
field_level	integer (0 \| 1)	Physics field complexity. 0 = real scalar (default). 1 = complex field (phase-aware, 62-di

Call it

curl

curl https://cracked-ai-pearl.vercel.app/v1/run \
  -H "Authorization: Bearer ck_live_..." -H "content-type: application/json" \
  -d '{"provider":"mcp-com-emergentphysicslab-waveguard","endpoint":"/waveguard_scan","input":{"training":[],"test":[]}}'

cli

npx cracked-ai run -p mcp-com-emergentphysicslab-waveguard -e /waveguard_scan -i '{"training":[],"test":[]}'

mcp

run_tool({ provider: "mcp-com-emergentphysicslab-waveguard", endpoint: "/waveguard_scan", input: {"training":[],"test":[]} })

Try it

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