Agent Memory Skill
SkillDocs & knowledgeLets your agent remember and search notes like decisions, architecture, and patterns across conversations.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Agent Memory Skill skill
About this capability
A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
What this skill tells your AI
The instructions your AI receives, as published by sickn33/agentic-awesome-skills in skills/agent-memory-mcp/SKILL.md and read by ahel’s review.
This skill provides a persistent, searchable memory bank that automatically syncs with project documentation. It runs as an MCP server to allow reading/writing/searching of long-term memories.
Prerequisites
- Node.js (v18+)
Setup
-
Review the Repository: Ask the user to approve network access to the named repository, then clone the pinned revision into a temporary directory, not an active skills path:
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-filesRead all bundled files and inspect
package.json, lockfiles, lifecycle scripts, network behavior, credential access, and filesystem scope. Show the findings and exact commit, then wait for explicit user approval. -
Install the Reviewed Revision:
Copy the reviewed tree to a user-selected location after approval. Install locked dependencies only after the package scripts have been reviewed:
cd <approved-agent-memory-directory> npm ci npm run compile -
Start the MCP Server: Use the helper script to activate the memory bank for your current project:
npm run start-server <project_id> <absolute_path_to_target_workspace>Example for current directory:
npm run start-server my-project $(pwd)
Capabilities (MCP Tools)
memory_search
Search for memories by query, type, or tags.
- Args:
query(string),type?(string),tags?(string[]) - Usage: "Find all authentication patterns" ->
memory_search({ query: "authentication", type: "pattern" })
memory_write
Record new knowledge or decisions.
- Args:
key(string),type(string),content(string),tags?(string[]) - Usage: "Save this architecture decision" ->
memory_write({ key: "auth-v1", type: "decision", content: "..." })
memory_read
Retrieve specific memory content by key.
- Args:
key(string) - Usage: "Get the auth design" ->
memory_read({ key: "auth-v1" })
memory_stats
View analytics on memory usage.
- Usage: "Show memory statistics" ->
memory_stats({})
Dashboard
This skill includes a standalone dashboard to visualize memory usage.
npm run start-dashboard <absolute_path_to_target_workspace>
Access at: http://localhost:3333
When to Use
This skill is applicable to execute the workflow or actions described in the overview.
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
- Re-review upstream before changing the pinned revision; a commit pin improves reproducibility but is not a trust guarantee.
Signals
- GitHub stars
- 46k
- Forks
- 7k
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
agent-memory-mcp-sickn33- Source
- github.com/sickn33/agentic-awesome-skills