0cb9ee5c58
- 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
36 lines
1.3 KiB
Markdown
36 lines
1.3 KiB
Markdown
# OpenClaw Skill
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MemPalace provides an official skill for [OpenClaw](https://github.com/openclaw/openclaw), making it trivial to give your ClawHub agents complete access to the palace's declarative memory and knowledge graph.
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## Installation
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The skill is built right into the `integrations/openclaw` directory of MemPalace.
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You can add MemPalace as an MCP server to OpenClaw via the CLI:
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```bash
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openclaw mcp set mempalace '{"command":"python3","args":["-m","mempalace.mcp_server"]}'
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```
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Or by directly editing your OpenClaw configuration:
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```json
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{
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"mcpServers": {
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"mempalace": {
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"command": "python3",
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"args": ["-m", "mempalace.mcp_server"]
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}
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}
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}
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```
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## How It Works
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Once connected, OpenClaw agents receive all 29 tools along with the **Memory Protocol**—a strict behavioral guide indicating they should:
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1. **Never guess**: Query `mempalace_search` or `mempalace_kg_query` before confidently answering.
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2. **Keep an agent diary**: Maintain continuity between sessions by writing to `mempalace_diary_write`.
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3. **Manage the Knowledge Graph**: Update declarative facts when things change using `mempalace_kg_add` and `mempalace_kg_invalidate`.
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By connecting OpenClaw to MemPalace, you get both autonomous code execution and persistent, high-recall memory in the same workflow.
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