# RLM-Mem MCP Server

> Use this tool when you need to analyze large codebases beyond 200k tokens, and traditional methods are insufficient. The RLM-Mem MCP Server solves the problem of limited context window sizes by storing content as variables and utilizing LLM-generated code for efficient search and analysis. It takes in large codebases as input and outputs actionable insights, making it ideal for complex codebase analysis and management tasks.

Canonical page: https://skillsregistry.net/skills/mosif16-rlm-mem-mcp  
JSON: https://api.skillsregistry.net/v1/skills/mosif16-rlm-mem-mcp

## Description

An MCP server implementing the TRUE Recursive Language Model technique for managing large context windows in Claude Code, enabling analysis of codebases beyond 200k tokens by storing content as variables and using LLM-generated code for search and analysis.

## Trust

- **Trust score (0–1):** 0.46
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/p2n02lpngc)
- **Repository:** <https://github.com/mosif16/RLM-Mem_MCP>

## 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": "mosif16-rlm-mem-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/mosif16-rlm-mem-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/mosif16-rlm-mem-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