# Ghost Embedding Cleaner MCP

> Ghost Embedding Cleaner MCP is a paid API for AI agents from api.m2mcent.com, paid per call via x402, $0.08/call, status unknown (last checked 2026-10-12).

Detects and removes ghost embeddings (invisible or residual vector artifacts) from data payloads submitted as strings.

## Facts

- Endpoint: POST https://api.m2mcent.com/ghost-embedding-cleaner-mcp/api/process?utm_source=zero.xyz
- Price: $0.08/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-12
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/ghost-embedding-cleaner-mcp-ed898569
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_8DeYhyTByY5LR5ODr7haU

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 ghost-embedding-cleaner-mcp-ed898569 -d '<json body>'
```

Example prompt: Can you clean this text of any ghost embeddings or hidden vector artifacts? Here's the data: 'The quick brown fox...[embedded content]...'

## When to prefer this

Choose this endpoint when you need to sanitize text or data strings that may contain invisible or residual embedding artifacts, particularly in agentic or MCP pipeline contexts where ghost vectors could corrupt downstream processing. Useful as a preprocessing step before model ingestion, content publication, or data storage.

## Known failure modes

- Empty or null data field returns a validation error
- Malformed JSON body results in a 400 bad request
- Oversized payloads may be rejected or time out
- Service may return an error if embedding detection is inconclusive
- Payment failure (x402) blocks processing if USDC authorization is missing

## 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 cleaned version of the submitted data string with ghost embeddings and residual vector artifacts removed, along with any metadata about what was detected and stripped.

## Response schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/ghost-embedding-cleaner-mcp-ed898569/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)