# com.clauxel.byterovermemory/byterovermemory-mcp

> Use this tool when you need to manage and monitor OpenAI Codex memory usage, as it provides remote access to verdicts, receipts, and usage logs. This tool solves problems related to tracking and controlling memory utilization, offering a paid solution for efficient resource management. It takes in memory-related queries and outputs detailed logs and receipts, making it ideal for applications requiring transparent and accountable memory usage.

Canonical page: https://skillsregistry.net/skills/com-clauxel-byterovermemory-byterovermemory-mcp  
JSON: https://api.skillsregistry.net/v1/skills/com-clauxel-byterovermemory-byterovermemory-mcp

## Description

A paid remote MCP for OpenAI Codex memory MCP, built to return verdicts, receipts, usage logs, and a

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-19

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/com.clauxel.byterovermemory%2Fbyterovermemory-mcp)
- **Repository:** <https://github.com/clauxel/byterover-team-memory-mcp>

## Use it

MCP endpoint published by the skill: `https://byterovermemory.clauxel.com/mcp`

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "com-clauxel-byterovermemory-byterovermemory-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/com-clauxel-byterovermemory-byterovermemory-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/com-clauxel-byterovermemory-byterovermemory-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt