a2a2p — Agent-to-Agent-to-Physical
AA
a2a2p — Agent-to-Agent-to-Physical
/get_supply_options

get supply options

Instant, synchronous pricing and lead time for a physical requirement — nothing is submitted or stored. Returns a deterministic parametric estimate (source="est

liveunknown~5s typical
mcpa2a2pagent-to-agent-to-physical
$0.0020
per call
plus $0.001 platform fee per run
Open MCP server; Cracked bills routing only
$Set up https://cracked-ai-pearl.vercel.app/SKILL.md, then use Cracked to run mcp-com-a2a2p-a2a2p /get_supply_options for me.

Input

FieldTypeDescription
requirementstringPlain-language description of the physical need. Maps to intent.purpose. Include function,
quantityintegerNumber of units needed. Maps to intent.quantity.
constraintsstringHard constraints: tolerances, certifications, materials to avoid, size/weight limits. Maps
budget_usdnumberApproximate budget in USD. Maps to intent.budget_envelope.
deadlinestringRequired delivery date or timeframe. Maps to intent.timeline.
contactstringOptional email or callback endpoint for quote delivery.
business_contextstringOptional business requirements (expected volumes, cost targets, ROI constraints). If provi
callback_urlstringOptional HTTPS URL. When the quote is ready, a2a2p POSTs it as JSON to this URL.
intentobjectLayer 1 — the problem. What the physical matter needs to DO. Use this for intent-driven re
specificationobjectLayer 2 — the solution. What the physical matter IS. Populate what is known. Precise speci
rejected_alternativesarrayOptions already considered and ruled out. Prevents re-suggesting and builds the learning c

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-a2a2p-a2a2p","endpoint":"/get_supply_options","input":{}}'
cli
npx cracked-ai run -p mcp-com-a2a2p-a2a2p -e /get_supply_options -i '{}'
mcp
run_tool({ provider: "mcp-com-a2a2p-a2a2p", endpoint: "/get_supply_options", input: {} })

Try it

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