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Amazinghorseli

Supercharged Dev

by Amazinghorseli
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Python
Remote

⚡ Supercharged Dev

Python License MCP

English · 中文

Your AI coder burns $200/month on junk tokens. This MCP server makes it think first, test first, compress first. 11 tools, one install.

The Problem

AI coding assistants are great at generating code fast. But:

Without Supercharged Dev

With Supercharged Dev

Jumps straight to code without clarifying what you actually want

Designs first — asks the right questions before writing a single line

Writes production code with no tests, hoping it works

Tests first — RED → GREEN → REFACTOR, every time

Guesses at bug fixes, changes random things, makes it worse

Debugs systematically — finds the root cause before touching anything

Submits PRs with no self-review, wasting your time

Reviews itself — 5-dimension check before showing you the diff

Burns tokens on verbose JSON, logs, and boilerplate

Compresses — saves 60–95% of tokens before they reach the LLM

Related MCP server: sumo-qa

What You Get (In One Picture)

You: "Add a login page"
      │
      ▼
AI calls brainstorm_design ──→ "Who are the users? What auth method?
                                What happens on failure? Let me propose 2 approaches..."
      │ (you approve the design)
      ▼
AI calls decompose_task ──→ Task 1: Create src/auth/login.tsx
                             Task 2: Add src/auth/__tests__/login.test.tsx
                             Task 3: Wire up route in app.tsx
                             (each task: 2-5 min, verifiable)
      │
      ▼
AI calls generate_test_skeleton ──→ "Here's a failing test for the login component.
                                     Run it first — it should fail. Then I'll implement."
      │ (test fails ✓)
      ▼
AI implements, then calls review_code_diff ──→ "Self-review:
                                                 ✓ Plan Compliance
                                                 ✓ Correctness
                                                 ⚠ Edge Cases — missing empty password case"
      │ (fixes the edge case)
      ▼
You get tested, reviewed, production-ready code.

When Do You Actually Use Each Tool?

Scenario

Tool to call

What happens

"I want to add a feature but I'm not sure about the approach"

brainstorm_design

Walks you through clarifying questions, proposes 2–3 approaches with tradeoffs

"I have a design doc, now make a plan"

decompose_task

Breaks it into 2–5 minute tasks. Each has a file path, code, and verification step

"Just wrote a bunch of code, is it any good?"

review_code_diff

5-dimension review. Critical issues block progress.

"Something's broken and I have no idea why"

debug_root_cause

4-phase process. Won't let you fix anything until you've proven the root cause.

"I need to write tests for this"

generate_test_skeleton

RED → GREEN → REFACTOR workflow. Test first, code second.

"This API response is 10,000 lines of JSON"

compress_content

Compresses to ~2,000 tokens. Same answer quality. Saves money.

"How much have I saved so far?"

compression_stats

Shows total tokens, savings %, cache hit rate, session runtime.

"What skills are available?"

list_skills

Shows all 13 Superpowers skills with descriptions and trigger conditions.

11 MCP Tools

🧠 Workflow (5 tools)

Tool

What it does

brainstorm_design

Socratic design exploration. Refuses to code until you've approved an approach.

decompose_task

Design spec → 2–5 min executable sub-tasks with file paths and verification steps.

review_code_diff

Self-review across 5 dimensions: Plan Compliance, Correctness, Testing, Edge Cases, Style.

debug_root_cause

4-phase debugging. Gate at each phase. No fixes until root cause is proven.

generate_test_skeleton

RED → GREEN → REFACTOR. Generates a failing test before you write any production code.

📖 Knowledge (3 tools)

Tool

What it does

get_skill

Returns the full Markdown of any Superpowers skill — injectable into any AI instruction.

list_skills

Lists all 13 available skills with descriptions. Discover what's possible.

get_preset_info

Shows what's in each preset (minimal/default/aggressive).

🔧 Compression (3 tools)

Tool

What it does

Typical savings

compress_content

Compresses content (Headroom or fallback). Auto-detects JSON/code/text.

50–92%

retrieve_original

Pulls original content back from LRU cache if the LLM needs it.

—

compression_stats

Live stats: total requests, tokens saved, cache hit rate, engine, uptime.

—

Skills Library (13 Skills)

#

Skill

Automatically triggers when...

1

brainstorming

You ask for any new feature or behavior change

2

writing-plans

A design has been approved

3

subagent-driven-development

Tasks need independent, isolated execution

4

executing-plans

You want batch execution with checkpoints

5

test-driven-development

Any production code is about to be written

6

systematic-debugging

A bug is reported

7

verification-before-completion

Someone claims a fix is done

8

requesting-code-review

A task is marked complete

9

receiving-code-review

Review feedback is received

10

using-git-worktrees

Code is about to be written in an existing project

11

finishing-a-development-branch

All tasks on a branch are done

12

dispatching-parallel-agents

Multiple independent modules need work

13

writing-skills

A new skill needs to be created

Who Is This For?

  • Solo developers who want the discipline of a senior engineering team in their AI assistant

  • Teams who want consistent code quality across AI-generated contributions

  • Anyone tired of $200+ Claude bills — compression pays for itself in a day

  • MCP power users who want one server that covers the full dev workflow

  • AI coding skeptics — add guardrails so the AI doesn't run wild

Quick Start

# 1. Install
pip install supercharged-dev

# 2. Start the MCP server
supercharged mcp serve

# 3. Print the config for your client
supercharged mcp config

Claude Desktop

{
  "mcpServers": {
    "supercharged": {
      "command": "uvx",
      "args": ["supercharged-dev", "mcp", "serve"]
    }
  }
}

Project Setup (Copies skill files + generates config)

cd your-project
supercharged init --preset aggressive

Presets

Preset

Skills

Compression

For

minimal

3

❌

Just the essentials: brainstorm, TDD, review

default

9

❌

Full workflow minus advanced features

aggressive

13

✅

Everything. Maximum discipline, minimum spend.

Compression (Optional Dependency)

pip install supercharged-dev[compress]

Content type

Typical savings

JSON API responses / MCP tool output

70–86%

Code search results (100 hits)

92%

Server logs

90%+

Full agent sessions (10+ tool calls)

85%

No quality loss — compressed content produces the same answers (verified on GSM8K, TruthfulQA, SQuAD).

中文说明

这是什么？

一个 MCP Server，让你的 AI 编程助手学会先思考再写代码、先测试再上线、先压缩再花钱。

它解决的问题：

没装之前

装了之后

AI 上来就写代码，不管你到底想要什么

先用苏格拉底式提问理清设计，批准后才动工

没有测试的保护，代码靠"祈祷"

TDD 铁律：RED → GREEN → REFACTOR

Debug 靠猜，改来改去越改越糟

系统化四阶段调试，找到根因前禁止修复

提 PR 不审查，浪费你时间

5 维度自审查，Critical 问题阻塞进度

JSON/日志/模板白白烧 Token

压缩 60–95%，答案质量不变，账单大幅下降

典型用法

当你想...

调用这个工具

会发生什么

加功能但不确定怎么做

brainstorm_design

挨个提问帮你理清需求，提 2–3 个方案让你选

把设计方案落地

decompose_task

拆成 2–5 分钟的小任务，每个都有文件路径和验证步骤

刚写的代码质量怎么样

review_code_diff

5 个维度逐一审查，Critical 问题会阻止继续

出 bug 了不知道原因

debug_root_cause

四阶段流程，不找到根因不准修复

需要写测试

generate_test_skeleton

先生成会失败的测试，然后写最少代码让它通过

API 返回了一万行 JSON

compress_content

压到 ~2000 token，省 70–86%，答案质量不变

想看省了多少钱

compression_stats

实时统计：总请求、Token 节省、缓存命中率

11 个 MCP 工具

类别

工具

一句话

🧠 工作流

brainstorm_design

写代码前先想清楚

🧠 工作流

decompose_task

设计 → 可执行任务

🧠 工作流

review_code_diff

5 维度自我审查

🧠 工作流

debug_root_cause

根因不明不修复

🧠 工作流

generate_test_skeleton

先写失败的测试

📖 知识

get_skill

读取任意 skill 文档

📖 知识

list_skills

列出全部 13 个 skill

📖 知识

get_preset_info

查看预设配置

🔧 压缩

compress_content

压缩省 Token

🔧 压缩

retrieve_original

从缓存取回原文

🔧 压缩

compression_stats

省钱统计

适合谁用？

  • 独立开发者 — 一个人也有团队的工程纪律

  • 团队 — 保证 AI 生成的代码质量一致

  • 心疼账单的人 — 压缩省的钱可能比工具本身贵得多

  • MCP 重度用户 — 一个 Server 覆盖完整开发流程

  • 对 AI 编程有顾虑的人 — 加上护栏，不让 AI 放飞自我

快速开始

pip install supercharged-dev
supercharged mcp serve

License

MIT · Built on Superpowers and Headroom.

This server cannot be installed

A
license - permissive license
-
quality - not tested
B
maintenance

How are these scores calculated?

Maintenance

–Maintainers
–Response time
–Release cycle
–Releases (12mo)
Commit activity

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