# Prompt Cache Hit Maximizer MCP

> Prompt Cache Hit Maximizer MCP is a paid API for AI agents from api.m2mcent.com, paid per call via x402, $0.03/call, status unknown (last checked 2026-10-11).

Optimizes prompt text to maximize cache hit rates in LLM inference systems by restructuring or transforming input data.

## Facts

- Endpoint: POST https://api.m2mcent.com/prompt-cache-hit-maximizer-mcp/api/process?utm_source=zero.xyz
- Price: $0.03/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-11
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/prompt-cache-hit-maximizer-mcp-fb88a65f
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_NtHuxAbNuIK8OiSsPBV29

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 prompt-cache-hit-maximizer-mcp-fb88a65f -d '<json body>'
```

Example prompt: Can you optimize this prompt so it maximizes cache hit rates in my LLM inference pipeline? Here's the prompt text: 'You are a helpful assistant. The user is asking about refund policies for order #12345.'

## When to prefer this

Choose this endpoint when you need to reduce LLM inference costs by improving prompt cache hit rates, especially for high-volume pipelines with repetitive or templated prompts. Prefer this when you have control over prompt structure and want to front-load static content for KV cache efficiency.

## Known failure modes

- Empty or missing 'data' field returns an error
- Malformed JSON input rejected
- Overly long input may be truncated or rejected
- Service may return generic output if prompt structure is not analyzable
- Payment failure via x402 protocol prevents processing

## How this service works

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## Output

Returns a restructured or transformed version of the input prompt/data string that is optimized for cache hit rates in LLM inference systems, potentially including reordered sections, normalized phrasing, or other structural modifications that improve cache reuse.

## Response schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/prompt-cache-hit-maximizer-mcp-fb88a65f/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)