# RLM Memory MCP Server

> Use this tool when you need to enable AI coding agents to retain memory of changes and discover relevant files across sessions. It provides persistent memory and semantic file discovery, solving problems of knowledge loss and file fragmentation in AI-driven coding workflows. Ideal for use cases where AI agents require continuity and context awareness, such as collaborative coding and project management.

Canonical page: https://skillsregistry.net/skills/jumpino27-rlm-memory-mcp-server  
JSON: https://api.skillsregistry.net/v1/skills/jumpino27-rlm-memory-mcp-server

## Description

Provides persistent memory and semantic file discovery for AI coding agents, enabling them to remember changes and find relevant files across sessions.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** file-system
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/yerrdztpoz)
- **Repository:** <https://github.com/jumpino27/RLM-Memory-MCP-Server>

## Use it

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": "jumpino27-rlm-memory-mcp-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/jumpino27-rlm-memory-mcp-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/jumpino27-rlm-memory-mcp-server/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