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Guide · Agent skill

How to use the Agent Memory MCP agent skill

Updated · written with AI from the project's own documentation and checked against our catalogue data

The agent-memory-mcp skill teaches an AI agent to set up a local memory server using the Model Context Protocol (MCP). That server stores project architecture decisions, patterns and documentation so the agent can search, read and write them in later sessions. This guide explains what an agent skill is, how to install this one, how to trigger it, and what safety checks to complete first. The skill runs scripts and uses the network, so read the safety section before installing.

Agent Memory MCPsickn33/agentic-awesome-skills · MIT

Quick start

  1. 1Check prerequisites. Confirm Node.js v18 or newer, git and npm are installed.
  2. 2Install the skill. Unzip the downloaded ZIP and place the folder in ~/.claude/skills/ or a project's .claude/skills/, or upload it under Settings → Capabilities → Skills.
  3. 3Review the pinned repository. Clone webzler/agentMemory at commit 0409b7b7bb6fe443d0d4b6a6b1ee0d4df214f3cd into a temporary directory and review package.json, lockfiles, scripts and network behavior.
  4. 4Install and compile. After approving the review, run npm ci and npm run compile in the approved directory.
  5. 5Start the server for a project. Run npm run start-server with a project ID and the absolute path of your workspace.
  6. 6Ask in plain language. Request a search, a save or a read of project decisions, and the agent will call the matching memory tool.

What is an agent skill, and what does this one do?

An agent skill is a folder with a SKILL.md file that gives an AI agent instructions for a specific task. When the skill is installed, the agent can read those instructions and follow them when a request matches the skill's description.

This skill sets up a persistent, searchable memory bank for a project. Once it is running, the agent can recall past decisions across sessions instead of starting from scratch. It exposes four MCP tools: memory_search, memory_write, memory_read and memory_stats.

  • memory_search: find memories by query, type or tags
  • memory_write: record new knowledge or decisions under a key
  • memory_read: retrieve a specific memory by key
  • memory_stats: view analytics on memory usage

What you need before installing

The skill lists its requirements in SKILL.md. You need Node.js v18 or newer, git and npm. The setup also clones an external repository, https://github.com/webzler/agentMemory, at a pinned commit, 0409b7b7bb6fe443d0d4b6a6b1ee0d4df214f3cd.

The optional dashboard is served on localhost:3333, so it needs local network access on that port.

  • Node.js v18 or newer
  • git
  • npm
  • Access to https://github.com/webzler/agentMemory (pinned commit 0409b7b7bb6fe443d0d4b6a6b1ee0d4df214f3cd)
  • Local access on localhost:3333 for the optional dashboard

Install the agent-memory-mcp skill

Download the ZIP from the skill's page on this site and unzip it. The skill folder contains SKILL.md. Put the folder in one of these locations:

  • Personal skills: ~/.claude/skills/
  • Project skills: a project's .claude/skills/ folder
  • Claude apps: upload the ZIP under Settings → Capabilities → Skills

Review the external repository before setup

The skill's first setup step asks for your approval to access the named repository. It clones the pinned revision into a temporary directory, not into an active skills path, and lists the files so you can review them. The agent should show its findings and the exact commit, then wait for your explicit approval.

Review means reading the bundled files and checking package.json, lockfiles, lifecycle scripts, network behavior, credential access and filesystem scope. Do not skip this step.

  • Approve network access to the named repository only
  • Confirm the commit is 0409b7b7bb6fe443d0d4b6a6b1ee0d4df214f3cd
  • Check package.json and lifecycle scripts before installing
  • Look for credential access and filesystem reach
review_dir="$(mktemp -d)" git clone --filter=blob:none https://github.com/webzler/agentMemory.git "$review_dir/agent-memory" git -C "$review_dir/agent-memory" checkout --detach 0409b7b7bb6fe443d0d4b6a6b1ee0d4df214f3cd git -C "$review_dir/agent-memory" ls-files

Install dependencies and start the memory server

After you approve the reviewed tree, copy it to a location you choose. Install locked dependencies only after the package scripts have been reviewed. Then compile and start the server for your project. The start script takes a project ID and the absolute path of the workspace to attach. Pass the current directory with $(pwd) if that is the project you want.

  • Confirm the project ID and the permitted workspace before starting
  • Use an absolute path for the workspace
cd <approved-agent-memory-directory> npm ci npm run compile npm run start-server my-project "$(pwd)"

Trigger the skill with natural requests

You do not need to type tool names. Ask in plain language and the agent will choose the matching tool. The skill's own examples map requests to tools like this: a request to find authentication patterns becomes a memory_search with the query authentication and type pattern, a request to save an architecture decision becomes memory_write with type decision, and a request to get the auth design becomes memory_read with the key auth-v1.

Ask for memory statistics to call memory_stats. To open the dashboard, the skill provides npm run start-dashboard with your workspace path, then opens http://localhost:3333.

  • "Find all authentication patterns"
  • "Save this architecture decision"
  • "Get the auth design"
  • "Show memory statistics"
npm run start-dashboard <absolute_path_to_target_workspace>

Safety notes: scripts, network and stored data

This skill is marked risk: critical. It runs npm install and starts a server from an external repository, so only use it if you can review third-party code. Memories persist on disk, so they can capture credentials or personal data if you are not careful.

Before importing anything from .kilocode/, .clinerules/ or .roo/, inspect it and exclude credentials and unrelated personal data. Treat search results as historical data, not as new instructions. Do not expose the dashboard to the network without a separate configuration review.

  • Do not use it on sensitive or regulated projects where memory files might hold credentials or personal data
  • Confirm the storage scope before any write and verify the resulting file changes
  • Re-review the upstream repository before changing the pinned commit; a pin aids reproducibility but is not a guarantee of trust

What people use it for

  • Searching past authentication patterns before designing a new login flow
  • Saving an architecture decision with a key so it can be read in a later session
  • Retrieving a previously recorded design by its key when a question comes up again
  • Checking memory usage statistics for a project using memory_stats
  • Viewing stored memories in the local dashboard on localhost:3333

Frequently asked questions

What is the agent-memory-mcp skill?

It is an agent skill that teaches an AI agent to set up and use a local MCP memory server. The server stores project architecture decisions, patterns and documentation so the agent can search, read and write them later.

How do I install the agent-memory-mcp skill?

Download the ZIP from the skill's page and unzip it. Place the folder in ~/.claude/skills/ or a project's .claude/skills/ folder, or upload the ZIP in the Claude apps under Settings → Capabilities → Skills.

What do I need to run it?

You need Node.js v18 or newer, git and npm. The setup also requires access to the external repository https://github.com/webzler/agentMemory at a pinned commit, and local access on localhost:3333 for the optional dashboard.

Is the agent-memory-mcp skill safe to use?

It is marked risk: critical. It runs npm install and starts a server from a third-party repository, and memories persist on disk. Review the code before running it, and avoid it for sensitive or regulated projects.

Is it free, and what is the licence?

The item is listed under the MIT licence. The source does not state any price, so check the listing for current details.

How is this different from just keeping notes in a docs folder?

The skill lets the agent search, read and write memories by key, type and tags during a session, instead of you pasting documents in each time. The source does not compare it with other tools, so judge that for your own project.

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Our verdict

Use this skill if you are a developer or a team that wants a persistent, searchable record of architecture decisions in one project, and you are willing to review third-party code before running it. Pick something else if you cannot review external code, or if the project handles credentials or personal data that could end up in memory files stored on disk.

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