# agent-memory-rs

> agent-memory-rs — kensave-agent-memory-rs. Use this tool when you need to implement efficient memory management for Large Language Model (LLM) agents, solving problems related to episodic and semantic memory storage and retrieval. It provides a comprehensive system with support for MCP servers and Kiro CLI, accepting input from various sources and outputting optimized memory structures. This tool is ideal for use cases requiring robust and scalable memory management in AI agent development.

Canonical page: https://skillsregistry.net/skills/kensave-agent-memory-rs  
JSON: https://api.skillsregistry.net/v1/skills/kensave-agent-memory-rs

## Description

Comprehensive memory management system for LLM agents implementing episodic, semantic. Built in Rust with MCP server support for Kiro CLI

## Trust

- **Trust score (0–1):** 0.48
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/kensave/agent-memory-rs)

## 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": "kensave-agent-memory-rs"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/kensave-agent-memory-rs` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/kensave-agent-memory-rs/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