Files
mempalace/website/guide/openclaw.md
T
Igor Lins e Silva 0cb9ee5c58 fix(website): correct false claims and stale numbers in live docs
- Landing: replace nonexistent `mempalace remember` CLI demo with real
  `mempalace mine ./notes`
- Landing: soften unverifiable absolutes ("forever available",
  "100% recall by design", "<50 ms", "90%+ compression",
  "two-thousand-year-old", "tens of thousands of entries")
- MCP tool count: 19 → 29 across mcp-integration, claude-code, openclaw,
  and modules; expand tool overview with Drawers, Tunnels, and System
  categories to match mcp_server.py
- Wake-up token range: ~170–900 → ~600–900 in cli/api-reference/python-api
  to match cli.py help text and concept docs
- Gemini CLI: move `--scope user` before target name and add `--`
  separator so `-m mempalace.mcp_server` isn't parsed as Gemini flags
2026-04-16 23:31:35 -03:00

1.3 KiB

OpenClaw Skill

MemPalace provides an official skill for OpenClaw, making it trivial to give your ClawHub agents complete access to the palace's declarative memory and knowledge graph.

Installation

The skill is built right into the integrations/openclaw directory of MemPalace.

You can add MemPalace as an MCP server to OpenClaw via the CLI:

openclaw mcp set mempalace '{"command":"python3","args":["-m","mempalace.mcp_server"]}'

Or by directly editing your OpenClaw configuration:

{
  "mcpServers": {
    "mempalace": {
      "command": "python3",
      "args": ["-m", "mempalace.mcp_server"]
    }
  }
}

How It Works

Once connected, OpenClaw agents receive all 29 tools along with the Memory Protocol—a strict behavioral guide indicating they should:

  1. Never guess: Query mempalace_search or mempalace_kg_query before confidently answering.
  2. Keep an agent diary: Maintain continuity between sessions by writing to mempalace_diary_write.
  3. Manage the Knowledge Graph: Update declarative facts when things change using mempalace_kg_add and mempalace_kg_invalidate.

By connecting OpenClaw to MemPalace, you get both autonomous code execution and persistent, high-recall memory in the same workflow.