mempalace-recall
Recall protocol for MemPalace — search the palace before answering about past work, people, projects, or prior decisions. Apply…
Install, configure, and operate MemPalace, including a private local palace, a shared-brain hub, or a client joining an existing hub. Use for first-time setup, MCP wiring, mining, status, palace audit and repair, wings, rooms, drawers, shared-brain identity, or logstream
Claude Code
$ npx -y skills add MemPalace/mempalace --skill mempalace --agent claude-code
Codex
$ npx skills add MemPalace/mempalace --skill mempalace -a codex -y
Cursor
$ npx skills add MemPalace/mempalace --skill mempalace -a cursor -y
Gemini CLI
$ npx skills add MemPalace/mempalace --skill mempalace -a gemini-cli -y
GitHub Copilot
$ npx skills add MemPalace/mempalace --skill mempalace -a github-copilot -y
OpenCode
$ npx skills add MemPalace/mempalace --skill mempalace -a opencode -y
Windsurf
$ npx skills add MemPalace/mempalace --skill mempalace -a windsurf -y
name: mempalace description: Install, configure, and operate MemPalace, including a private local palace, a shared-brain hub, or a client joining an existing hub. Use for first-time setup, MCP wiring, mining, status, palace audit and repair, wings, rooms, drawers, shared-brain identity, or logstream readiness.
A guided, skill-first setup for a searchable memory palace. The user may have installed this skill with `npx skills add` before the MemPalace Python package or MCP server exists; that is the normal bootstrap path.
check. Do not assume that an installed Python package is reachable on PATH.
rebuild an existing palace just to make setup simpler.
Prefer an isolated `uv` tool installation:
uv tool install mempalace
If `uv` is unavailable, use the PATH-visible Python installation:
python -m pip install mempalace
After installation, run `mempalace --version`. If it still is not reachable, fix PATH or use the matching `uv tool run` invocation before continuing.
Ask which outcome they want unless it is already clear:
1. **private local palace** — one machine, local stdio MCP; 2. **shared-brain hub** — this machine owns the palace and serves the fleet; 3. **client joining an existing hub** — this machine connects to a hub owned elsewhere.
Also ask which project or conversation corpus should be initialized, offering the current working directory as the default. A shared-brain client does not initialize a second copy of the owner's palace.
MemPalace provides dynamic, version-correct instructions via the CLI. To get instructions for any operation:
mempalace instructions <command>
Where `<command>` is one of: `help`, `init`, `mine`, `search`, `status`.
Run the appropriate instructions command, then follow the returned instructions step by step.
For a new local palace or hub, follow `mempalace instructions init`, configure the selected corpus, then verify with `mempalace status`. For a client, skip local initialization and obtain the hub URL and bearer token from the user.
For local stdio integrations, use the command printed by `mempalace mcp`. Typical registrations are:
claude mcp add mempalace -- mempalace-mcp codex mcp add mempalace -- mempalace-mcp
For a shared-brain hub, guide the user through `mempalace serve` and the [official shared-brain guide](https://mempalaceofficial.com/guide/shared-brain.html). Do not expose a non-loopback server without authentication. For a client joining an existing hub, configure the harness's HTTP MCP transport with the supplied bearer token; never print or store that token in project instructions, drawers, or logstream events.
Restart or reconnect the harness when required, then verify that the live MCP tool list includes MemPalace tools. Package installation alone is not proof that MCP is connected.
When shared-brain mode is selected:
(machine), harness family (`claude`, `codex`, `grok`, `antigravity`, …), and the current workspace as project. Two windows in the same project are one actor.
mempalace rules --host <host> --harness <harness> --project <example>
Default `--mcp full` matches the 47-tool `mempalace-mcp` server this skill registers. If the user opted into `mempalace-light-mcp`, re-render with `--mcp light` instead. Replace an existing `<!-- mempalace-shared-brain -->` block instead of appending a duplicate.
instructions (Claude `~/.claude/CLAUDE.md`, Codex `~/.codex/AGENTS.md`, Grok `~/.grok/AGENTS.md`, Antigravity `~/.gemini/config/GEMINI.md`).
equivalent MCP event-list call.
before long tasks and do **not** arm a watcher at session start. Arm `mempalace logstream watch --agent <host>:<harness>:<project>` (the CLI defaults a sanitized `--state-file`) only when the user asked to listen, the agent claimed a task, or it delegated. A remote-only MCP client must instead loop on `mempalace_event_wait`, preserving the last event id as `since_event_id`; never point it at a local SQLite watcher. Explain any permission allowlisting needed. If it cannot maintain either loop, record that the agent is turn-based and must sweep its MCP inbox with `mempalace_event_list` on wake-up.
Do not post a test event without telling the user: logstream events are immutable. If the user approves a smoke event, address it narrowly and close the loop with an acknowledgement.
Summarize the installed version, palace location or hub URL (without secrets), MCP connection, stable agent identity, watcher mode, and the first safe next action. For active delegation, hand off to the `mempalace-task` skill.
Ask whether the user wants weekly stable-release checks. The default is no. Explain that enabling them contacts PyPI but sends no palace content, identity, or telemetry. When enabling, record the installer actually used with `mempalace update configure --enable --installer uv-tool` (or `pipx` / `pip`); use `--disable` to opt out. Checks never install anything. In `mempalace_status`, treat `updates.server` as the palace-serving runtime and `updates.client` (when present) as the local proxy runtime; do not conflate
Local-first AI memory. Verbatim storage, pluggable backend, 96.6% R@5 raw on LongMemEval — zero API calls.
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Install, configure, and operate MemPalace, including a private local palace, a shared-brain hub, or a client joining an existing…