GPU Capacity Auctioneer MCP

x402

GPU Capacity Auctioneer MCP is a paid API for AI agents from api.m2mcent.com, paid per call via x402, $0.05/call, status unknown (last checked 2026-10-16).

Runs an auction to allocate GPU compute capacity among competing bidders, returning winning bids and allocation results.

Price / call$0.05

Seller volume →—

Success—

StatusUnknown

How this service works

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Output

Returns structured auction results including winning bids, allocated GPU capacities, assigned time slots, bidder rankings, and any unallocated capacity or rejected bids.

Example use cases

AI training job GPU allocation

“I need to auction off 16 H100 GPU slots for 6 hours tonight starting at midnight — run the capacity auction and tell me the winning bids and which jobs get assigned.”

Cost-optimal GPU procurement

“I have a budget of $1.80 per GPU-hour and need at least 4 A100s for a 2-hour inference run this afternoon — submit that as a bid into the GPU capacity auction and show me if I win.”

Multi-tenant GPU scheduling

“We have 32 GPUs free this weekend and three teams competing for them — run an auction with their bids and give me the allocation plan showing who gets what capacity and when.”

Technical details

Endpoint

POSThttps://api.m2mcent.com/gpu-capacity-auctioneer-mcp/api/process?utm_source=zero.xyz

When to prefer

Choose this endpoint when you need to programmatically run a market-based auction to allocate scarce GPU compute resources among competing workloads or tenants, especially when price discovery and fair allocation are required. Prefer over static scheduling when demand is variable and bidders have heterogeneous valuations.

Side effects

Malformed data string input returns a 400 validation error
No bids submitted or insufficient capacity data leads to empty auction result
Conflicting bid constraints may result in partial allocation
Service unavailability returns 402 or 5xx HTTP error
Invalid GPU type or capacity parameters cause processing failure

Output

Schema · Response

{
  "type": "json",
  "example": {
    "success": true
  }
}

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