# MCP-RLM

> Use this tool when you need to process and reason about massive documents with millions of tokens, and require a cost-effective and accurate approach to natural language understanding. The MCP-RLM tool takes in long-form documents and decomposes them into sub-queries, outputting informed responses through its recursive language model architecture. It is ideal for use cases involving large-scale text analysis and reasoning, where traditional language models may be inefficient or ineffective.

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

## Description

An implementation of the Recursive Language Models architecture that enables AI agents to process massive documents by programmatically decomposing them into sub-queries. It allows for cost-effective and accurate reasoning across millions of tokens by treating long-form data as an external environment for root and worker models.

## 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:** [Glama](https://glama.ai/mcp/servers/kwu8okcssa)
- **Repository:** <https://github.com/MuhammadIndar/MCP-RLM>

## 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": "muhammadindar-mcp-rlm"
    }
  }
}
```

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

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