# Semantic Drift Detector MCP

> Semantic Drift Detector MCP is a paid API for AI agents from api.m2mcent.com, paid per call via x402, $0.2/call, status unknown (last checked 2026-10-11).

Detects semantic drift in text data, identifying when meaning, tone, or conceptual direction has shifted from a reference baseline.

## Facts

- Endpoint: POST https://api.m2mcent.com/semantic-drift-detector-mcp/api/process?utm_source=zero.xyz
- Price: $0.2/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-11
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/semantic-drift-detector-mcp-1e190abf
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_Yf4YLPlPvd1MAnMgoAhNH

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability semantic-drift-detector-mcp-1e190abf -d '<json body>'
```

Example prompt: Check this block of text for semantic drift — here's the content: 'Our platform has evolved from a simple task manager into a comprehensive enterprise workflow orchestration suite with AI-driven automation at its core.' I want to know if and how much the meaning has shifted from a straightforward productivity tool framing.

## When to prefer this

Choose this endpoint when you need to programmatically detect whether text, AI outputs, or documents have shifted in meaning, tone, or conceptual focus over time or revisions. It is particularly useful for AI monitoring pipelines, content quality assurance workflows, and catching when language models begin producing semantically inconsistent outputs. Prefer it over general-purpose text analysis when the specific question is about drift or deviation from a prior meaning baseline.

## Known failure modes

- Empty or null 'data' field returns validation error
- Text too long may exceed processing limits
- Ambiguous or very short input may produce low-confidence drift scores
- No baseline reference may limit comparative drift analysis
- Non-textual binary data passed as string will produce meaningless results

## 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 an analysis of the input text indicating whether semantic drift has been detected, the degree of drift, which concepts or themes have shifted, and potentially a structured drift score or report identifying the nature of the meaning deviation.

## Response schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/semantic-drift-detector-mcp-1e190abf/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from api.m2mcent.com](https://www.zero.xyz/host/api.m2mcent.com/llms.txt)