# memnos

> memnos — thameema-memnos. Use this tool when you need to provide persistent memory for AI coding agents, enabling them to store and recall information across sessions. Memnos solves the problem of ephemeral memory in AI agents, allowing for more efficient and effective coding workflows. It offers a REST API, Python SDK, and integration with popular LLM agents, accepting code and data as inputs and outputting stored memories and recalled information.

Canonical page: https://skillsregistry.net/skills/thameema-memnos  
JSON: https://api.skillsregistry.net/v1/skills/thameema-memnos

## Description

Persistent memory for AI coding agents — MCP server, REST API & Python SDK. Works with Claude Code, Cursor, Windsurf and any LLM agent.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** Apache-2.0
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/thameema/memnos)

## 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": "thameema-memnos"
    }
  }
}
```

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