agent-memory-mcp

A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).

5 stars

Best use case

agent-memory-mcp is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).

Teams using agent-memory-mcp should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/agent-memory-mcp/SKILL.md --create-dirs "https://raw.githubusercontent.com/FrancoStino/opencode-skills-collection/main/bundled-skills/agent-memory-mcp/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/agent-memory-mcp/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How agent-memory-mcp Compares

Feature / Agentagent-memory-mcpStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# 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:

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

2. **Install Dependencies**:

   ```bash
   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:

   ```bash
   npm run start-server <project_id> <absolute_path_to_target_workspace>
   ```

   _Example for current directory:_

   ```bash
   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.

```bash
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.

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