# Vector Dimension Compressor MCP

> Vector Dimension Compressor MCP is a paid API for AI agents from api.m2mcent.com, paid per call via x402, $0.12/call, status unknown (last checked 2026-10-10).

Compresses high-dimensional vector data into lower-dimensional representations for efficient storage, retrieval, and processing.

## Facts

- Endpoint: POST https://api.m2mcent.com/vector-dimension-compressor-mcp/api/process?utm_source=zero.xyz
- Price: $0.12/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-10
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/vector-dimension-compressor-mcp-a0a78b6c
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_g40qEW8aGqsbnjAT0gas2

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 vector-dimension-compressor-mcp-a0a78b6c -d '<json body>'
```

Example prompt: Can you compress these high-dimensional vector embeddings for me so they take up less space and are faster to search through? Here's the data: [0.23, 0.87, 0.12, ...]

## When to prefer this

Use this endpoint when you need to reduce the size or dimensionality of high-dimensional vector embeddings or feature vectors, especially before storing them in vector databases or using them in latency-sensitive retrieval pipelines. Prefer this over manual PCA or UMAP scripts when you need a fast, API-accessible compression step in an agentic workflow.

## Known failure modes

- Invalid or malformed data string returns a 400 error
- Empty data field causes processing failure
- Data format not recognized as valid vector representation
- Payment not completed results in 402 response
- Server timeout on very large vector payloads

## 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 compressed, lower-dimensional representation of the submitted vector data, suitable for more efficient storage, similarity search, or downstream ML inference.

## Response schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/vector-dimension-compressor-mcp-a0a78b6c/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)