# Embedding Model Migrator MCP

> Embedding Model Migrator MCP is a paid API for AI agents from api.m2mcent.com, paid per call via x402, $0.5/call, status unknown (last checked 2026-10-11).

Migrates embeddings or embedding configurations from one model to another, enabling vector space transitions across model versions or providers.

## Facts

- Endpoint: POST https://api.m2mcent.com/embedding-model-migrator-mcp/api/process?utm_source=zero.xyz
- Price: $0.5/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-11
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/embedding-model-migrator-mcp-29215f04
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_Av7Qz7rOgJ55GRkIhxRMW

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 embedding-model-migrator-mcp-29215f04 -d '<json body>'
```

Example prompt: I need to migrate my existing embeddings from text-embedding-ada-002 to text-embedding-3-large — can you run the migration on this embedding data and give me the converted vectors?

## When to prefer this

Choose this endpoint when you need to programmatically migrate embedding vectors from one model to another without manually re-encoding all source documents, especially when the source data is already embedded and re-embedding from scratch is costly or impractical.

## Known failure modes

- Malformed or invalid embedding data in the 'data' field causing a 400 error
- Unsupported source or target model combination resulting in a processing error
- Data too large for a single request causing timeout or payload limit errors
- Incompatible vector dimensionality between source and target models
- Payment failure via x402 protocol preventing request processing

## 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 transformed or migrated embedding vectors compatible with the target embedding model, along with any mapping metadata or migration status information indicating successful conversion.

## Response schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/embedding-model-migrator-mcp-29215f04/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)