Satori Aligner MCP

x402

Satori Aligner MCP is a paid API for AI agents from api.m2mcent.com, paid per call via x402, $0.05/call, status unknown (last checked 2026-10-15).

Processes input data through a satori-aligner pipeline, likely performing alignment, calibration, or normalization of agent or model outputs.

Price / call$0.05

Seller volume →—

Success—

StatusUnknown

How this service works

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Output

Returns a processed and aligned version of the submitted data string, with alignment or calibration applied by the satori-aligner pipeline. The exact response structure is not documented, but likely includes the transformed output and possibly alignment metadata or a confidence signal.

Example use cases

Agent output alignment check

“Take this agent-generated summary and run it through the satori aligner to make sure it's properly aligned and calibrated before I send it to the client.”

Normalize raw model response

“I have this raw output from my language model — can you process it through the satori aligner to normalize it? The text is: 'User satisfaction scores varied significantly across demographic groups.'”

Pre-publication data calibration

“Before I publish this analysis report, please pass the following data string through the satori aligner to apply alignment calibration: 'Q3 revenue projections indicate a 15% growth trajectory assuming stable market conditions.'”

Technical details

Endpoint

POSThttps://api.m2mcent.com/satori-aligner-mcp/api/process?utm_source=zero.xyz

When to prefer

Choose this endpoint when you need to apply satori-style alignment or calibration to a data string as part of an agentic pipeline. Prefer it over generic text processing APIs when your workflow specifically requires the satori-aligner normalization step, or when downstream systems expect satori-aligned outputs.

Side effects

Empty or missing 'data' field returns validation error
Malformed JSON body results in 400 Bad Request
Payment not attached or insufficient USDC balance triggers 402 Payment Required
Service unavailable or pipeline error returns 500
Oversized input string may be rejected or truncated

Output

Schema · Response

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

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