# project-brain-mcp

> Use this tool when you need to optimize code development by preventing redundant problem-solving and preserving architectural decisions across sessions and projects. It takes in project data and code history as inputs, and outputs optimized code development pathways, streamlining the engineering process. Ideal for use in collaborative coding environments and large-scale projects where efficiency and consistency are crucial.

Canonical page: https://skillsregistry.net/skills/pym2282-project-brain-mcp  
JSON: https://api.skillsregistry.net/v1/skills/pym2282-project-brain-mcp

## Description

Engineering memory for Claude Code — prevents re-investigating solved problems and repeating rejected architectural decisions across sessions and projects.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/iuhcpsv8p2)
- **Repository:** <https://github.com/pym2282/project-brain-mcp>

## 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": "pym2282-project-brain-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/pym2282-project-brain-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/pym2282-project-brain-mcp/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