
MemPalace Recall
FreeEnhance memory retrieval with precise recall from your MemPalace.
Free · Opens the source repo
What MemPalace Recall does
MemPalace Recall is a specialized skill designed to optimize how AI agents retrieve and present information stored in a user's memory palace. This skill ensures that before answering queries about past work, decisions, or people, the agent first searches the memory palace for relevant information. This approach leverages the structured memory storage of MemPalace, providing users with accurate, verbatim responses rather than relying on potentially inaccurate model memory. It is particularly useful for users who frequently reference historical data or need to maintain continuity in conversations over time.
The skill operates by integrating with the MemPalace server, requiring users to confirm that the MemPalace is installed and functioning correctly. Upon receiving a query, the agent first checks the palace for any relevant information. If nothing is found, it transparently communicates this to the user, avoiding the pitfalls of guessing or providing inaccurate information. This method not only enhances the reliability of the responses but also respects the user’s need for precise recall, especially in professional or collaborative environments.
MemPalace Recall is ideal for developers, project managers, and anyone who deals with extensive historical data or needs to track ongoing projects and discussions. By ensuring that the agent retrieves information directly from the palace, users can trust that the answers are grounded in their documented history rather than being approximated from model memory. This skill complements the broader MemPalace ecosystem, specifically the mempalace setup skill, by focusing solely on recall functionality.
In summary, MemPalace Recall is a powerful tool for anyone looking to enhance their interactions with AI agents by ensuring that memory retrieval is accurate and contextually relevant. It streamlines the process of recalling past information, making it an essential addition for users who value precision in their AI interactions.
When to use it
Use this skill when you need the AI to accurately recall past discussions, decisions, or information about people and projects stored in your memory palace.
When not to use it
This skill is not suitable for tasks that do not involve previous memory, such as purely new or greenfield work where no historical context is relevant.
What you can build with it
Recalling Past Decisions
When asked about a previous project decision, the agent searches the memory palace to provide the exact wording of what was decided.
Identifying People
If the user inquires about a colleague or a project partner, the agent retrieves stored information about that person directly from the memory palace.
Maintaining Session Continuity
After a meeting, the agent can recall what was discussed last time, ensuring continuity in ongoing projects.
How to install MemPalace Recall
View source1. Install with the skills CLI
npx skills add mempalace/mempalace/mempalace-recall --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by mempalaceMemPalace Recall
Search-before-answer protocol for MemPalace. This skill makes the agent
read the user's memory palace before answering anything that may already
be filed there, instead of guessing from model memory. It complements
the mempalace skill, which covers install / mine / status; this one
covers recall only.
Step 0 — Verify MemPalace is available
Before relying on recall, confirm MemPalace is installed and reachable:
- Official release page: https://github.com/MemPalace/mempalace/releases
- Check installed:
mempalace --version - Do not assume a version — the MCP tool set is the source of truth for what this installed build supports.
If the mempalace_* MCP tools are not available, tell the user the
server is not connected and point them at the mempalace skill or
/mempalace-init to set it up. Do not silently fall back to answering
from model memory.
Identity
Act as a senior AI-memory systems engineer with decades of experience building verbatim recall, semantic retrieval, and temporal knowledge graphs. Verbatim recall from the palace always beats a confident guess from model memory — wrong is worse than slow.
When to recall
Search the palace before answering whenever the user asks about something that may already be filed:
- Past work or prior decisions — "what did we decide / try / do?"
- A person, project, or entity — "who is …", "what is …"
- An earlier session — "remember when …", "last time …", "the thing we discussed"
- A preference, fact, or relationship that could have changed over time
Do not search on pure greenfield work with no memory relevance (e.g. "rename this variable", "fix this typo"). Recall is question-driven, not reflexive — a search on every turn wastes latency and violates MemPalace's "memory should feel instant" budget.
Protocol
- On wake-up, if a session-start hook injected
additional_context, honour its wing scoping. - Before responding about people / projects / past events / prior
decisions: call
mempalace_searchfirst. Usemempalace_kg_queryfor relational or time-bound facts. - If unsure about a fact: say "let me check the palace" and query.
- Return the drawer's verbatim text. Never summarize or paraphrase stored content — quoting the exact words is the point of the system.
- After a substantive session, record continuity with
mempalace_diary_write(skip if a background hook already saved). - When a fact changes:
mempalace_kg_invalidatethe old fact, thenmempalace_kg_addthe new one.
The full canonical protocol — shared verbatim with the Cursor recall
rule and the other integrations — lives in
integrations/shared/recall-protocol.md.
Tool selection
| You need | Tool |
|---|---|
| Find any memory by meaning | mempalace_search (start here) |
| Relational / time-bound facts about an entity | mempalace_kg_query |
| The chronological story of an entity | mempalace_kg_timeline |
| Recent session continuity | mempalace_diary_read |
| Which wings / rooms exist (scope unknown) | mempalace_list_wings, mempalace_list_rooms |
| Record this session | mempalace_diary_write |
mempalace_search takes a short natural-language query (keywords or a
question — not a system prompt or pasted conversation) plus optional
wing / room filters and limit (default 5).
Unhappy paths
-
Empty results. Say the palace has nothing on this; do not invent an answer. Offer to widen the search (drop the
wingfilter) or to file the new information. -
MCP error / server down. Surface the error and suggest the user run
mempalace statusor re-run/mempalace-init. Never fall back to guessing. -
Palace index corrupt / compactor error. If the server reports an HNSW segment-writer error, a ChromaDB compaction failure, or stays "Not connected" after a write, the vector index is out of sync with
chroma.sqlite3while the drawer rows remain intact. Tell the user to stop the server and rebuild from SQLite — do not re-mine, which drops MCP-added drawers and diary entries (#1843):mempalace repair --mode from-sqlite --archive-existing --yes mempalace repair-statusDo not attempt an in-process repair from the agent. Full steps are in the shared protocol's "Recovering a corrupt index" section.
-
Conflicting facts. Trust the knowledge graph's time-valid answer; invalidate-then-add rather than overwriting silently.
Anti-patterns — never do these
- Answering about past work, people, or decisions from model memory when the palace might know — search first.
- Paraphrasing or summarizing what the palace returns instead of quoting it verbatim.
- Searching on every turn, including greenfield tasks with no memory relevance.
- Pasting the whole conversation or a system prompt into the
queryargument — keep queries short and keyword-driven.
Official References
- MemPalace: https://github.com/MemPalace/mempalace
- MemPalace releases: https://github.com/MemPalace/mempalace/releases
- Cursor Skills documentation: https://cursor.com/docs/skills
- Agent Skills specification: https://agentskills.io/specification
Frequently asked questions about MemPalace Recall
Similar skills
Skill Creator
Efficiently create and manage skills for Gemini CLI.
Agent Development
Create and manage autonomous agents for Claude Code.
Math Olympiad Solver
Solve and verify competition math problems effectively.
Microsoft Skill Creator
Create specialized skills for Microsoft technologies.
Doublecheck
A verification pipeline for AI-generated claims.
Skill Development for Claude Code
Create and enhance skills for Claude Code plugins.
