# agentmem

> agentmem — josan88-agentmem. Use this tool when you need to retain contextual information across interactions, enabling AI agents to learn from past experiences and make informed decisions. It solves problems of knowledge retention and recall, allowing agents to store and retrieve memories through a command-line interface or MCP integration. Ideal for use cases requiring persistent memory, such as conversational dialogue or task-oriented learning.

Canonical page: https://skillsregistry.net/skills/josan88-agentmem  
JSON: https://api.skillsregistry.net/v1/skills/josan88-agentmem

## Description

Enables AI coding agents to store and retrieve persistent contextual memories locally, with support for tagging and querying through CLI or MCP integration.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** api-integration
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/o7acn8ilgc)
- **Repository:** <https://github.com/Josan88/agentmem>

## 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": "josan88-agentmem"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/josan88-agentmem` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/josan88-agentmem/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