memory-tools

A set of rules for using a saved project memory store. It tells the coding agent when to look up, save, change, or remove information about past decisions and conventions.

In plain words
What is it for?
It helps maintain architecture decisions, coding conventions, bug findings, performance notes, and other project-specific context.
Why use it?
It reduces repeated explanations and helps the agent remember important project context between conversations. It also limits saved information to useful, non-temporary notes.

Cursor rule for Cursor

Install

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.

agentmods
npx agentmods add rules/labforgedev/copilot-memory-mcp/memory-tools
Clone the repo
git clone --depth 1 https://github.com/LabForgeDev/copilot-memory-mcp

Made for: Cursor.

Per session 276 This file is loaded in full into every session.
When invoked 276 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00276 $0.00276
Opus 5 $0.00138 $0.00138
Sonnet 5 $0.00055 $0.00055
Haiku 4.5 $0.00028 $0.00028

Measured yesterday against content hash 2506f0c0d0eb, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

memory-tools 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 yesterday.

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.

examples/.cursor/rules/memory-tools.mdc · 27 lines

What it actually says

You have access to a persistent memory MCP server (copilot-memory) at http://localhost:8000/sse.

Available tools

Tool When to use
create_memory Save a new decision, convention, or finding
search_memories Retrieve relevant context before answering
update_memory Amend an existing memory when something changes
delete_memory Remove stale or incorrect memories
list_memories Browse all saved memories for a project

Rules

  1. Always search before answering questions about architecture, conventions, or past decisions — call search_memories first.
  2. Always save new architectural decisions, agreed conventions, and non-obvious workarounds.
  3. Set project_name to the current repository name on every call.
  4. Prefer update_memory over delete + recreate when content changes.
  5. Use consistent tags: architecture, convention, bug, performance, devops, security, testing, tooling.
  6. Do not save temporary debug notes or information already obvious from the code.
Changes

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.

  1. yesterday First seen · 27 lines · 276 tokens per session scan A 2506f0c0d0eb

Subscribe to this mod's changes

memory-tools is a cursor rule published in the GitHub repository LabForgeDev/copilot-memory-mcp (3 stars, last pushed 5mo ago), licensed MIT. It adds 276 tokens to every session, about $0.0014 per session on Opus 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 2026-08-31.