| name | memory-palace |
| description | Manage durable cross-session memory via Memory Palace MCP server. Supports semantic search, write guards, and hierarchical memory organization. Use for saving facts, recalling context, and managing long-term knowledge. Chinese triggers: 记忆, 长期记忆, 记住, 回忆, 召回, 压缩上下文, 重建索引. |
Memory Palace
Durable, semantically-searchable memory system for AI agents. Persists knowledge across sessions via a local MCP server.
Setup: See Memory Palace repository for installation. Requires Ollama with an embedding model (recommended: snowflake-arctic-embed2).
First Action in Any Session
Always start with:
read_memory("system://boot")
This loads core memories and recent context.
Core Workflow
- Boot:
read_memory("system://boot")
- Search:
search_memory(query, include_session=true) if URI is unknown
- Read:
read_memory(uri) to inspect the exact target
- Mutate:
create_memory or update_memory only after reading
- Maintain:
compact_context or rebuild_index when needed
Key Rules
- Read before write: Always read existing memory before creating/updating
- Respect guards: If
guard_action=NOOP, stop and inspect the suggested target before proceeding
- Prefer update over create: Use
update_memory when a related memory already exists
- Fresh context: In new sessions or subagents, always reload with
system://boot
Available Tools
| Tool | Purpose |
|---|
read_memory | Read a memory by URI |
search_memory | Semantic search across all memories |
create_memory | Create a new memory |
update_memory | Update an existing memory |
delete_memory | Delete a memory |
add_alias | Add an alternative URI for a memory |
compact_context | Distill noisy session history |
rebuild_index | Rebuild the semantic search index |
index_status | Check index health |
Common URIs
system://boot — Session initializationsystem://index — Full memory indexsystem://recent — Recently modified memoriescore://agent — Agent identity and rulescore://my_user — User profile
