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- name: io.github.holetron-lab/fleet-memory -> ai.rcll/fleet-memory DNS-verified namespace on a domain we renew ourselves. The io.github.* namespace is authorised by a GitHub account; io.github.holetron died with a suspended account and is unrecoverable. Do not repeat that exposure. - description: 176 -> 95 chars. ServerDetail.description has maxLength 100; the previous value would have been rejected at publish time. - repository.id: pinned to GitHub repo id 1344503808 (resurrection-attack guard - the id changes if a repo is deleted and recreated). - repository.url stays on github.com: the registry validator hard-matches ^https?://(www\.)?github\.com/... or gitlab.com and rejects anything else, so the canonical forge URL cannot go in this field. rcll.ai carries it instead (websiteUrl), and the site names the forge as canonical. - mcp-server/package.json mcpName must equal the server name exactly; the registry reads it from the PUBLISHED npm version metadata, so this had to change before the first publish, not after. |
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RCLL MCP Server (fleet-memory-mcp)
Standalone MCP server that exposes RCLL memory tools to any MCP-compatible client (Claude Code, OpenClaw, etc). RCLL is self-hosted, hierarchical shared memory for a team of AI agents — topic-scoped rooms, L0–L3 depth, pgvector under the hood. The published artifact is named fleet-memory; RCLL is the product name.
RCLL — team memory for agent fleets. Built on Hindsight (github.com/vectorize-io/hindsight, MIT).
Canonical repository: https://godcrm.ai/git/holetron-lab/fleet-memory — self-hosted, clonable anonymously. https://github.com/holetron-lab/fleet-memory is a read-only mirror of it, and is where issues and stars go.
RCLL is a fork of vectorize-io/hindsight (MIT). It keeps Hindsight's storage engine and adds rooms — topic scoping over one shared store, which is selectivity rather than isolation — plus a hierarchical depth model (L0–L3). The room/hall/layer taxonomy is prior art in the hierarchical-memory space; the implementation here is our own.
Tools
| Tool | Description |
|---|---|
memory_retain |
Save memories with room/hall/layer classification |
memory_recall |
Scoped semantic search with room filtering |
memory_reflect |
Deep reasoning + synthesis over stored memories |
memory_compress |
Create closet summaries from accumulated facts |
memory_bridge |
Cross-bank tunnels between related memories |
Quick Start
npx fleet-memory-mcp
FLEET_URL points at your own RCLL backend (default http://127.0.0.1:5100); this package is the
MCP client half and does not start a store for you. Standing one up is the quickstart on
rcll.ai.
From a clone instead:
cd mcp-server
npm install
FLEET_URL=http://localhost:5100 node server.js
Claude Code
Add to ~/.claude/mcp.json:
{
"mcpServers": {
"rcll": {
"command": "npx",
"args": ["-y", "fleet-memory-mcp"],
"env": {
"FLEET_URL": "http://localhost:5100",
"FLEET_BANK": "my-agent-bank"
}
}
}
}
Environment Variables
| Variable | Default | Description |
|---|---|---|
FLEET_URL |
http://127.0.0.1:5100 |
fleet-memory backend base URL |
FLEET_BANK |
fleet-main |
Default memory bank ID. Set it explicitly. |
Migrating from hindsight-mempalace-mcp
That package defaulted to bank mempalace-main. fleet-memory-mcp defaults to fleet-main,
so an install that never set the variable would open a different, empty bank — which
reads as "the update erased my memory". It does not: the old bank is still there.
Set FLEET_BANK=mempalace-main to keep reading it, or move the contents into a new
bank first. When FLEET_BANK and MEMPALACE_BANK are both unset, the server prints
which bank it defaulted to on stderr rather than picking one silently.
Deprecated (still read, with a notice on stderr)
Installs created before the rebrand keep working — these are used only when the
FLEET_* equivalent is unset, and they will be dropped in a future major.
| Legacy variable | Replaced by |
|---|---|
HINDSIGHT_URL |
FLEET_URL |
MEMPALACE_BANK |
FLEET_BANK |
Memory Taxonomy
Rooms (topics): auth, pipeline, schema, infrastructure, ui, api, deployment, monitoring, agent, general
Halls (knowledge types — the hall field): fact, event, decision, preference, discovery, procedure, warning
Layers (depth):
- L0 — Surface / identity (always at hand)
- L1 — Critical (recalled by default)
- L2 — Session (default for new memories)
- L3 — Deepest burrow / archive (deep search only, compressed into closets)