# RLM MCP Server

> Use this tool when you need to analyze large datasets exceeding 100MB without contextual limitations. It enables efficient data processing by storing information in external variables via a sandboxed Python REPL, preventing context pollution and token limit issues. Ideal for handling massive files, this tool provides a scalable solution for data analysis and processing.

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

## Description

Enables the analysis of massive datasets by storing data in external variables via a sandboxed Python REPL instead of the model's context window. This allows users to process files larger than 100MB without polluting the context or hitting token limits.

## Trust

- **Trust score (0–1):** 0.00
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** file-system
- **Updated:** 2026-09-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/u8yk1ybl59)
- **Repository:** <https://github.com/delonsp/rlm-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": "delonsp-rlm-mcp-server"
    }
  }
}
```

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