/agent-memory-mcp

name: agent-memory-mcp
description: "A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions)."
risk: unknown
source: community
date_added: "2026-02-27"

Agent Memory Skill

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

1. **Clone the Repository**: Clone the `agentMemory` project into your agent's workspace or a parallel directory:

   git clone https://github.com/webzler/agentMemory.git .agent/skills/agent-memory

2. **Install Dependencies**:

   cd .agent/skills/agent-memory
   npm install
   npm run compile

3. **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.