AR
Amit Rathiesh
@mayurrathi
⭐ 40.7k GitHub stars

Agent Memory Mcp

Agent Memory Mcp is an data AI skill with a core value of A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions). It helps developers solve real-world problems in the data domain, boosting efficiency, automating repetitive tasks, and optimizing workflows.

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

Last verified on: 2026-07-07

Quick Facts

Category data
Works With Claude
Source sickn33/antigravity-awesome-skills
Stars ⭐ 40.7k
Last Verified 2026-07-07
Risk Level Low
mkdir -p ./skills/agent-memory-mcp && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/agent-memory-mcp/SKILL.md -o ./skills/agent-memory-mcp/SKILL.md

Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).

Skill Content

# 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.

🎯 Best For

  • Claude users
  • Data professionals
  • Analytics teams
  • Researchers

💡 Use Cases

  • Data pipeline auditing
  • Query optimization

📖 How to Use This Skill

  1. 1

    Install the Skill

    Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.

  2. 2

    Load into Your AI Assistant

    Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.

  3. 3

    Apply Agent Memory Mcp to Your Work

    Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.

  4. 4

    Review and Refine

    Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.

❓ Frequently Asked Questions

How do I install Agent Memory Mcp?

Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/agent-memory-mcp/SKILL.md, ready to use.

Can I customize this skill for my team?

Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.

⚠️ Common Mistakes to Avoid

Ignoring data quality

AI analysis inherits all data quality issues — profile your data first.

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