MemPalace is a local-first AI memory system that stores conversation history verbatim and retrieves relevant passages through semantic search. It is for AI-agent users who want searchable, structured memory on their own machine, with a replaceable retrieval backend.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/MemPalace/mempalaceWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/rules/mempalace/mempalace/mempalace-recall)<a href="https://agentmods.dev/rules/mempalace/mempalace/mempalace-recall"><img src="https://agentmods.dev/badge/rules/mempalace/mempalace/mempalace-recall/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/rules/mempalace/mempalace/mempalace-recall"><img src="https://agentmods.dev/badge/rules/mempalace/mempalace/mempalace-recall.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00066 | $0.00252 |
| Opus 5.5 | $0.00026 | $0.00101 |
| Sonnet 5.5 | $0.00013 | $0.00050 |
| Haiku 4.5 | $0.00007 | $0.00025 |
Grade A, and why
mempalace-recall scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
MemPalace recall
Before answering anything that may already be in the user's memory palace — past work, prior decisions, a person, a project, or "what did we do / decide / discuss last time?" — search the palace first:
- Call
mempalace_searchwith a short keyword query. Usemempalace_kg_queryfor relational or time-bound facts. - Quote the drawer's verbatim text. Never summarize or paraphrase stored content.
- If results are empty, say so — do not invent an answer. If the MCP server is unavailable, surface the error; do not fall back to guessing.
Skip recall for pure greenfield work with no memory relevance (renaming a variable, fixing a typo). Recall is question-driven, not reflexive.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 21 lines · 66 tokens per session scan A 2284b82feb38
mempalace-recall is a cursor rule published in the GitHub repository MemPalace/mempalace (59,584 stars, last pushed today), licensed MIT. It adds 66 tokens to every session and 252 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other cursor rules, from other repositories
02-python-standards
Python coding standards, libraries, and concurrency safety.
react-vite-tanstack
You are an expert in TypeScript, Node.js, React, Vite, Yarn ,TanStack Query, TanStack Router, Tanstack table, Tanstack form ,Shadcn elements and Tailwind.
004_auto_context
Rules for requesting relevant memory context based on file types, locations, and current activity.
ponytail
Ponytail, lazy senior dev mode. Always pick the simplest solution that works.
angular-20
This rule provides comprehensive best practices and coding standards for Angular development, focusing on modern TypeScript, standalone components, signals, and performance optimizations.
dev-standard
Apache Superset development standards and guidelines for Cursor IDE.