# Volatility 3 Memory Forensics

> Use this tool when you need to analyze memory forensics data using natural language inputs, solving problems such as investigating malicious activity or detecting hidden threats. It takes in natural language queries and outputs forensic analysis results, leveraging the Volatility 3 Framework and Large Language Models. Ideal for use cases where complex memory analysis needs to be performed efficiently and effectively.

Canonical page: https://skillsregistry.net/skills/bornpresident-volatility  
JSON: https://api.skillsregistry.net/v1/skills/bornpresident-volatility

## Description

This project bridges the powerful memory forensics capabilities of the Volatility 3 Framework with Large Language Models (LLMs) through the Model Context Protocol (MCP). It allows you to perform memory forensics analysis using natural language by exposing Volatility plugins as MCP tools that can be invoked directly by Claude or other MCP-compatible LLMs.

## Trust

- **Trust score (0–1):** 0.53
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/bornpresident-volatility)
- **Repository:** <https://github.com/bornpresident/volatility-mcp-server>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "bornpresident-volatility"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/bornpresident-volatility` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/bornpresident-volatility/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt