# RCLL

> RCLL — ai-rcll-fleet-memory. Use this tool when you need to enable seamless communication and knowledge sharing among a team of AI agents. RCLL provides a self-hosted shared memory solution, allowing agents to access and contribute to a hierarchical knowledge base with rooms and depth levels L0-L3, without relying on large language models for data retrieval. Ideal for applications requiring efficient and scalable agent collaboration, RCLL streamlines information exchange and facilitates coordinated decision-making.

Canonical page: https://skillsregistry.net/skills/ai-rcll-fleet-memory  
JSON: https://api.skillsregistry.net/v1/skills/ai-rcll-fleet-memory

## Description

Self-hosted shared memory for a team of AI agents. Rooms, L0-L3 depth, no LLM on the read path.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** unverified

## Facts

- **Version:** 0.1.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-02

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/ai.rcll%2Ffleet-memory)
- **Repository:** <https://github.com/Holetron-lab/fleet-memory>

## 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": "ai-rcll-fleet-memory"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ai-rcll-fleet-memory` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ai-rcll-fleet-memory/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