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Sybil Graph Clustering MCP
x402
Sybil Graph Clustering MCP is a paid API for AI agents from api.m2mcent.com, paid per call via x402, $0.1/call, status unknown (last checked 2026-10-23).
Detects and clusters sybil identities in a graph network by analyzing relational patterns to identify coordinated fake or fraudulent accounts.
Price / call$0.1
Success—
StatusUnknown
How this service works
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Output
Returns cluster assignments identifying groups of nodes (accounts, identities, or wallets) that exhibit coordinated or sybil-like behavior, allowing the caller to flag or filter fraudulent entities from the network.
Example use cases
Detecting bots in social platform
“I have a graph of follower/following relationships from my platform and I think there are coordinated bot accounts inflating follower counts — can you run sybil graph clustering on this data to find the suspicious clusters?”
Blockchain airdrop sybil filtering
“Here's my on-chain transaction graph from our token airdrop — I need to detect sybil wallets that are farming the airdrop by acting as fake independent accounts. Cluster them so I can filter them out.”
DAO voting manipulation detection
“I want to check whether our DAO governance votes are being manipulated by sybil identities. Here's the voting interaction graph — can you cluster it to identify groups that look like they're coordinated fake voters?”
Technical details
Endpoint
POSThttps://api.m2mcent.com/sybil-graph-clustering-mcp/api/process?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need to detect coordinated fake, fraudulent, or sybil identities within a graph-structured dataset — particularly for social networks, blockchain address graphs, or DAO voting graphs where account coordination fraud is a concern. Prefer this over generic anomaly detection when the relationship graph structure is the primary signal.
Side effects
- Malformed or empty graph data input returns an error
- Insufficiently connected graph may yield no meaningful clusters
- Very large graphs may time out or require chunked input
- Missing edge/node structure in the data string causes parsing failure
Output
Schema · Response
{
"type": "json",
"example": {
"success": true
}
}Tags
x402
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