# nous

> Use this tool when you need to retain and recall project-specific knowledge and insights for AI assistants, enabling efficient querying and teaching of concepts, decisions, and patterns. It solves problems of knowledge loss and duplication of effort by storing information in a persistent SQLite database. Ideal for use cases requiring cumulative learning and memory, such as iterative project development and continuous improvement.

Canonical page: https://skillsregistry.net/skills/vlados-nous  
JSON: https://api.skillsregistry.net/v1/skills/vlados-nous

## Description

Provides a persistent project memory for AI assistants via MCP tools, enabling querying and teaching of concepts, decisions, and patterns stored in an SQLite database.

## Trust

- **Trust score (0–1):** 0.63
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/tawlvdl0sq)
- **Repository:** <https://github.com/vlados/nous>

## 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": "vlados-nous"
    }
  }
}
```

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