# nobrainr

> nobrainr — vicquick-nobrainr. Use this tool when you need to manage persistent memory and knowledge graphs for AI agents, solving problems of data retention and retrieval in complex AI systems. It integrates PostgreSQL, pgvector, and Ollama via MCP, accepting input data and outputting structured knowledge graphs. Utilize nobrainr in contexts where AI agents require reliable, long-term memory and information retrieval capabilities.

Canonical page: https://skillsregistry.net/skills/vicquick-nobrainr  
JSON: https://api.skillsregistry.net/v1/skills/vicquick-nobrainr

## Description

Persistent memory and knowledge graph for AI agents via MCP — PostgreSQL + pgvector + Ollama

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/vicquick/nobrainr)

## 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": "vicquick-nobrainr"
    }
  }
}
```

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