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Build a Persistent, Searchable Agent Memory

MCP server skill that provides persistent, searchable memory storage with four core tools for read/write/search operations and a visualization dashboard.

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Antigravity
Maintainer?
46
Spark score
out of 100
Updated 2 days ago
Version 13.1.0
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Why it matters

Establish a long-term memory for your AI agent that automatically syncs with project documentation, enabling efficient knowledge retrieval and management.

Outcomes

What it gets done

01

Create a searchable memory bank for AI agents.

02

Automatically sync agent memories with project documentation.

03

Read, write, and search long-term memories via MCP tools.

04

Visualize memory usage with a dedicated dashboard.

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/ag-agent-memory-mcp | bash

Capabilities

What this skill does

RAG index

Chunks, embeds, and indexes documents for semantic retrieval.

Knowledge graph

Builds and queries entity-relationship graphs.

Extract

Pulls structured data fields from unstructured text.

Summarize

Condenses long documents or threads into key takeaways.

Overview

Agent Memory Skill

What it does

A Node.js-based MCP server that provides persistent memory storage with search, read, write, and analytics capabilities, plus a web dashboard for visualization.

How it connects

Use when you need agents to store and retrieve project-specific knowledge, decisions, patterns, or documentation in a structured, searchable format.

Source README

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.

Discussion

Questions & comments · 0

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