# brain-ecosystem

> brain-ecosystem — timmeck-brain-ecosystem. Use this tool when you need to manage and optimize self-learning monorepo servers for efficient code management. It solves problems related to code repository complexity and scalability by providing a brain-ecosystem for Claude Code. The tool takes git inputs and outputs optimized server configurations, ideal for use in large-scale codebase development and maintenance contexts.

Canonical page: https://skillsregistry.net/skills/timmeck-brain-ecosystem  
JSON: https://api.skillsregistry.net/v1/skills/timmeck-brain-ecosystem

## Description

Brain Ecosystem — Self-learning MCP servers for Claude Code (monorepo)

## Trust

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

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-20

## Source

- **Source listing:** [GitHub](https://github.com/timmeck/brain-ecosystem)

## 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": "timmeck-brain-ecosystem"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/timmeck-brain-ecosystem` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/timmeck-brain-ecosystem/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