# RLM MCP Server

> Use this tool when you need to process long contexts with limited large language models (LLMs), as it enables recursive decomposition to handle arbitrarily long inputs without relying on external LLM APIs, solving context length limitations and improving model efficiency. It takes in long contexts and decomposes them into manageable segments, outputting processed results. Ideal for use cases where context length is a constraint, such as text analysis or generation tasks.

Canonical page: https://skillsregistry.net/skills/win10ogod-rlm-mcp  
JSON: https://api.skillsregistry.net/v1/skills/win10ogod-rlm-mcp

## Description

Enables any LLM to process arbitrarily long contexts through recursive decomposition, without requiring external LLM APIs.

## Trust

- **Trust score (0–1):** 0.69
- **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/ur2jdrt4lc)
- **Repository:** <https://github.com/win10ogod/RLM-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": "win10ogod-rlm-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/win10ogod-rlm-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/win10ogod-rlm-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