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skills/agent-memory-mcp/SKILL.md
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skills/agent-memory-mcp/SKILL.md
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name: agent-memory-mcp
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author: Amit Rathiesh
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description: A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
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---
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# Agent Memory Skill
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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.
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## Prerequisites
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- Node.js (v18+)
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## Setup
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1. **Clone the Repository**:
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Clone the `agentMemory` project into your agent's workspace or a parallel directory:
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```bash
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git clone https://github.com/webzler/agentMemory.git .agent/skills/agent-memory
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```
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2. **Install Dependencies**:
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```bash
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cd .agent/skills/agent-memory
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npm install
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npm run compile
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```
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3. **Start the MCP Server**:
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Use the helper script to activate the memory bank for your current project:
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```bash
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npm run start-server <project_id> <absolute_path_to_target_workspace>
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```
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_Example for current directory:_
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```bash
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npm run start-server my-project $(pwd)
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```
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## Capabilities (MCP Tools)
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### `memory_search`
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Search for memories by query, type, or tags.
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- **Args**: `query` (string), `type?` (string), `tags?` (string[])
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- **Usage**: "Find all authentication patterns" -> `memory_search({ query: "authentication", type: "pattern" })`
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### `memory_write`
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Record new knowledge or decisions.
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- **Args**: `key` (string), `type` (string), `content` (string), `tags?` (string[])
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- **Usage**: "Save this architecture decision" -> `memory_write({ key: "auth-v1", type: "decision", content: "..." })`
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### `memory_read`
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Retrieve specific memory content by key.
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- **Args**: `key` (string)
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- **Usage**: "Get the auth design" -> `memory_read({ key: "auth-v1" })`
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### `memory_stats`
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View analytics on memory usage.
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- **Usage**: "Show memory statistics" -> `memory_stats({})`
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## Dashboard
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This skill includes a standalone dashboard to visualize memory usage.
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```bash
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npm run start-dashboard <absolute_path_to_target_workspace>
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```
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Access at: `http://localhost:3333`
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