Skip to content
TrustedSkillsbeta
Back to all skills

Memory Mcp

Checked
d-o-hub·vlatest·agents·MIT

Provides MCP tools guidance and assistance for orchestrating AI agents and multi-step workflows.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

Installs under a different name. Its SKILL.md names it do-memory-mcp, not the name it is listed under, so the command below uses that name.
  1. 1

    Run this in your project

    terminal
    $ npx skills add d-o-hub/rust-self-learning-memory --skill do-memory-mcp -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

d-o-hub

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned d-o-hub/rust-self-learning-memory at da7210f59b.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
da7210f59b
Manifest
.agents/skills/do-memory-mcp/SKILL.md
Scanned
8 files, 590 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The memory-mcp skill provides a mechanism for AI agents to store and retrieve information using a self-learning memory system. This allows agents to retain context across multiple interactions, learn from past experiences, and adapt their behavior accordingly. It utilizes a Rust-based implementation for efficient memory management and processing.

When to use it

  • Long Conversations: Use when the agent needs to remember details discussed earlier in a lengthy conversation.
  • Task Sequencing: When an agent is performing multi-step tasks, this skill can help track progress and dependencies.
  • Personalized Interactions: To enable agents to learn user preferences over time and tailor responses accordingly.
  • Complex Problem Solving: For scenarios requiring the agent to recall previous attempts or information gathered during troubleshooting.

Key capabilities

  • Self-learning memory system
  • Rust implementation for efficiency
  • Context retention across interactions
  • Adaptive behavior based on past experiences

Example prompts

  • "Remember that I prefer my coffee with oat milk."
  • "What was the last step we took in solving this problem?"
  • "Based on our previous conversations, what's my favorite author?"

Tips & gotchas

The skill’s effectiveness depends on providing clear and concise information during interactions. While it learns over time, initial prompts should be explicit to establish a baseline for the memory system.