Self-Evolving MCP Brain

A self-updating MCP (Model Context Protocol) system: analyze design/code inputs with an LLM, converse to refine them, then crystallize approved patterns into a local skill library that MCP agents can read.

Components

| File | Role | Port | |---|---|---| | mcp_server.py | FastMCP server; exposes skills://rhythm-standards resource | (stdio MCP) | | ui_server.py | FastAPI backend — bridges UI ↔ freellmapi proxy | 8000 | | frontend_server.py | Static server for the Vue 3 SPA | 3000 | | freellmapi_client.py | Raw-HTTP client for the freellmapi proxy (no OpenAI SDK) | — | | frontend/index.html | Vue 3 chat UI + code preview | — | | .mcp_skills/ | Crystallized skills library (read by the MCP resource) | — |

Prerequisites

1. Python 3.10+ (built on 3.12).
2. The freellmapi proxy running locally on http://localhost:3001

(it is a Node/Docker app, not a Python package).

1. A unified key from the proxy's Keys page.

Setup

python3 -m venv .venv && . .venv/bin/activate
pip install -r requirements.txt
cp .env.example .env        # then edit FREELLMAPI_KEY
set -a; source .env; set +a # export env vars into your shell

Run (Phase 2)

# Terminal A — UI backend
python ui_server.py          # :8000

# Terminal B — frontend
python frontend_server.py    # :3000

Open http://localhost:3000.

Phase status

• Phase 1 ✅ MCP server + resource.
• Phase 2 ✅ Conversational analyzer UI + freellmapi integration.
• Phase 3 ✅ Crystallization pipeline (APPROVE & CRYSTALLIZE button).
• Phase 4 ✅ End-to-end test with a real link.