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Deadlock Resolver MCP
x402
Deadlock Resolver MCP is a paid API for AI agents from api.m2mcent.com, paid per call via x402, $0.02/call, status unknown (last checked 2026-10-16).
Detects and resolves deadlock conditions in concurrent systems, processes, or workflows by analyzing dependency graphs and cycle patterns
Price / call$0.02
Success—
StatusUnknown
How this service works
The premier global index of 1,069 monetized MCP nodes across 205 specialized subdomains. Gasless USDC runtime settlements via x402 V2 Spec on Base L2. Save 95% token context.
Output
Returns a resolution plan or analysis identifying the deadlock cycle, the involved processes or resources, and a recommended strategy to break the deadlock (e.g. which process to preempt, rollback, or reschedule).
Example use cases
Database transaction deadlock resolution
“Two database transactions are stuck — transaction T1 holds a lock on table Orders and is waiting for table Inventory, while T2 holds Inventory and is waiting for Orders. Analyze this deadlock and tell me which transaction to roll back and why.”
Multithreaded application hang diagnosis
“My Java application has frozen and I suspect a deadlock between threads. Thread 1 holds mutex A and is waiting for mutex B, thread 2 holds mutex B and waiting for mutex C, and thread 3 holds mutex C and waiting for mutex A. Can you detect the deadlock cycle and recommend a resolution strategy?”
Distributed microservice circular dependency fix
“My microservices are deadlocked: Service X is waiting for a response from Service Y before releasing its lock, and Service Y is waiting for Service X to release first. Please analyze this circular wait and suggest how to break it.”
Technical details
Endpoint
POSThttps://api.m2mcent.com/deadlock-resolver-mcp/api/process?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need automated detection and resolution advice for deadlock conditions in concurrent systems, database transactions, distributed workflows, or multithreaded applications. Prefer this over manual analysis when dependency graphs are complex or when you need a fast, programmatic recommendation.
Side effects
- Malformed or incomplete dependency data returns a parsing error
- Ambiguous input that doesn't clearly describe process-resource relationships may yield low-confidence results
- Very large or complex dependency graphs may time out
- Input that doesn't represent a true deadlock scenario may return 'no deadlock detected'
Output
Schema · Response
{
"type": "json",
"example": {
"success": true
}
}Tags
x402
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