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agent-memory-mcp

为AI智能体提供持久可检索知识管理的混合记忆系统（架构、模式与决策）。

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name:agent-memory-mcpauthor:Amit Rathieshdescription:A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).

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

  • 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

  • Install Dependencies:

    • cd .agent/skills/agent-memory
       npm install
       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