<img src="assets/icon.png" width="48" height="48" align="top" style="margin-right: 10px;"> MCP Creator Growth
A context-aware Model Context Protocol (MCP) server that acts as a learning sidecar for AI coding assistants. It helps developers learn from AI-generated code changes through interactive quizzes and provides agents with a persistent project-specific debugging memory.
🌐 Resources
| Resource | Description |
|---|---|
| Glama MCP Marketplace | Official MCP server listing with installation guides |
| DeepWiki Documentation | AI-generated deep analysis of the codebase |
| GitHub Repository | Source code, issues, and contributions |
🚀 Why Use This?
| For | Benefit |
|---|---|
| Developers | Don't just accept AI code—understand it. Request a quiz to verify your grasp of the logic, security, or performance implications. |
| AI Agents | Stop solving the same bug twice. The server quietly records debugging solutions and retrieves them automatically when similar errors occur. |
📦 Available Tools
| Tool | Type | Description |
|---|---|---|
learning_session | 🎓 Interactive | Opens a WebUI quiz based on recent code changes. Blocks until user completes learning. |
debug_search | 🔍 Silent RAG | Searches project debug history for relevant past solutions. Auto-triggered on errors. |
debug_record | 📝 Silent | Records debugging experiences to project knowledge base. Auto-triggered after fixes. |
term_get | 📚 Reference | Fetches programming terms/concepts. Tracks shown terms to avoid repetition. |
Tool Details
<details> <summary><b>🎓 learning_session</b> - Interactive Learning Card</summary>Trigger: User explicitly requests (e.g., "Quiz me", "Test my understanding")
Parameters:
| Parameter | Type | Default | Description |
|---|---|---|---|
project_directory | string | "." | Project directory path |
summary | string | — | Structured summary of Agent's actions |
reasoning | object | null | 5-Why reasoning (goal, trigger, mechanism, alternatives, risks) |
quizzes | array | auto-generated | 3 quiz questions with options, answer, explanation |
focus_areas | array | ["logic"] | Focus areas: logic, security, performance, architecture, syntax |
timeout | int | 600 | Timeout in seconds (60-7200) |
Returns: {"status": "completed", "action": "HALT_GENERATION"}
Trigger: Auto-called when encountering errors (silent, no UI)
Parameters:
| Parameter | Type | Default | Description |
|---|---|---|---|
query | string | — | Error message or description to search |
project_directory | string | "." | Project directory path |
error_type | string | null | Filter by error type (e.g., ImportError) |
tags | array | null | Filter by tags |
limit | int | 5 | Maximum results (1-20) |
Returns: {"results": [...], "count": N}
Trigger: Auto-called after fixing bugs (silent, background)
Parameters:
| Parameter | Type | Default | Description |
|---|---|---|---|
context | object | — | Error context: {error_type, error_message, file, line} |
cause | string | — | Root cause analysis |
solution | string | — | Solution that worked |
project_directory | string | "." | Project directory path |
tags | array | null | Tags for categorization |
Returns: {"ok": true, "id": "..."}
Available Domains: programming_basics, data_structures, algorithms, software_design, web_development, version_control, testing, security, databases, devops
Parameters:
| Parameter | Type | Default | Description |
|---|---|---|---|
project_directory | string | "." | Project directory path |
count | int | 3 | Number of terms (1-5) |
domain | string | null | Filter by domain |
Returns: {"terms": [...], "count": N, "remaining": N}
🛠️ Installation
One-Line Install (Recommended)
<table> <tr> <th>Platform</th> <th>Command</th> </tr> <tr> <td><b>macOS / Linux</b></td> <td>curl -fsSL https://raw.githubusercontent.com/SunflowersLwtech/mcp_creator_growth/main/scripts/install.sh | bashirm https://raw.githubusercontent.com/SunflowersLwtech/mcp_creator_growth/main/scripts/install.ps1 | iexThe installer will:
- Auto-detect your Python environment (uv → conda → venv)
- Clone the repository to
~/mcp-creator-growth - Create virtual environment and install dependencies
- Print the exact command to configure your IDE
Manual Installation
<details> <summary>Click to expand manual installation steps</summary>Prerequisites: Python 3.11+ or uv
# 1. Clone the repository
git clone https://github.com/SunflowersLwtech/mcp_creator_growth.git
cd mcp_creator_growth
# 2. Create virtual environment and install
# Using uv (recommended)
uv venv --python 3.11 mcp-creator-growth
source mcp-creator-growth/bin/activate # macOS/Linux
# mcp-creator-growth\Scripts\activate # Windows
uv pip install -e '.[dev]'
# Or using standard venv
python -m venv mcp-creator-growth
source mcp-creator-growth/bin/activate # macOS/Linux
# mcp-creator-growth\Scripts\activate # Windows
pip install -e '.[dev]'Docker Installation
<details> <summary>Click to expand Docker installation steps</summary>Prerequisites: Docker installed on your system
# 1. Pull from Docker Hub
docker pull sunflowerslwtech/mcp-creator-growth:latest
# Or build locally
git clone https://github.com/SunflowersLwtech/mcp_creator_growth.git
cd mcp_creator_growth
docker build -t mcp-creator-growth .
# 2. Run with Docker
docker run -i mcp-creator-growth
# 3. Or use Docker Compose
docker-compose up -dFor detailed Docker usage, persistent storage, and Claude Desktop integration, see DOCKER.md.
</details>⚙️ IDE Configuration
Claude Code (CLI) — One Command Setup
After installation, configure your AI coding IDE to use this MCP server.
Claude Code
Option 1: CLI (Recommended)
# macOS / Linux
claude mcp add mcp-creator-growth -- ~/mcp-creator-growth/mcp-creator-growth/bin/mcp-creator-growth
# Windows
claude mcp add mcp-creator-growth -- %USERPROFILE%\mcp-creator-growth\mcp-creator-growth\Scripts\mcp-creator-growth.exeOption 2: Config File
Add to ~/.claude.json:
{
"mcpServers": {
"mcp-creator-growth": {
"command": "~/mcp-creator-growth/mcp-creator-growth/bin/mcp-creator-growth"
}
}
}For Windows:
{
"mcpServers": {
"mcp-creator-growth": {
"command": "C:\\Users\\YourName\\mcp-creator-growth\\mcp-creator-growth\\Scripts\\mcp-creator-growth.exe"
}
}
}Example paths:
- Unix (uv):
~/mcp-creator-growth/mcp-creator-growth/bin/mcp-creator-growth - Windows (uv):
C:\\Users\\YourName\\mcp-creator-growth\\mcp-creator-growth\\Scripts\\mcp-creator-growth.exe - Windows (conda):
C:\\Users\\YourName\\anaconda3\\envs\\mcp-creator-growth\\Scripts\\mcp-creator-growth.exe
Path breakdown (Unix example):
~/mcp-creator-growth→ repository directorymcp-creator-growth→ virtual environment directory created by uv/venvbin/mcp-creator-growth→ executable
Cursor
Add to Cursor MCP settings (Settings → MCP → Add Server):
{
"mcp-creator-growth": {
"command": "~/mcp-creator-growth/mcp-creator-growth/bin/mcp-creator-growth"
}
}For Windows:
{
"mcp-creator-growth": {
"command": "C:\\Users\\YourName\\mcp-creator-growth\\mcp-creator-growth\\Scripts\\mcp-creator-growth.exe"
}
}Windsurf
Add to ~/.codeium/windsurf/mcp_config.json:
{
"mcpServers": {
"mcp-creator-growth": {
"command": "~/mcp-creator-growth/mcp-creator-growth/bin/mcp-creator-growth"
}
}
}Docker Configuration
To use Docker with any MCP-compatible IDE:
{
"mcpServers": {
"mcp-creator-growth": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-v",
"/path/to/your/project:/workspace",
"-w",
"/workspace",
"mcp-creator-growth"
]
}
}
}See DOCKER.md for detailed Docker configuration examples for Claude Desktop, Cursor, and other IDEs.
Other IDEs
For any MCP-compatible IDE, use these settings:
- Command:
<install-path>/mcp-creator-growth/bin/mcp-creator-growth(ormcp-creator-growth\Scripts\mcp-creator-growth.exeon Windows) - Transport: stdio
After configuration, restart your IDE.
Usage
Available Tools
| Tool | Trigger | For | Returns |
|---|---|---|---|
learning_session | User explicit request | User | {status, action} - minimal |
debug_search | Automatic (on error) | Agent | Compact summaries |
debug_record | Automatic (after fix) | Agent | {ok, id} - minimal |
For Users: Learning Session
Say to your AI assistant:
- "Quiz me on this change"
- "Test my understanding"
- "Help me learn about what you did"
The agent will create an interactive learning card and wait until you complete it.
Note: Quiz scores are saved locally for your self-tracking but are NOT returned to the agent - this keeps the context clean.
For Agents: Debug Tools
The debug tools work silently in the background:
- Search first: When encountering errors, agent searches past solutions
- Record after: When fixing errors, agent records the solution
- Progressive disclosure: Returns compact summaries, not full records
- Fast lookups: Uses inverted index for keyword-based searches
Updating
One-Line Update (Recommended)
The remote update script automatically detects your installation and works with any path format (including Chinese/non-ASCII paths):
<table> <tr> <td><b>macOS / Linux</b></td> <td>curl -fsSL https://raw.githubusercontent.com/SunflowersLwtech/mcp_creator_growth/main/scripts/update.sh | bashirm https://raw.githubusercontent.com/SunflowersLwtech/mcp_creator_growth/main/scripts/update.ps1 | iexThe update script will:
- Auto-detect your installation location (supports multiple installations)
- Pull the latest changes from the repository
- Force-reinstall dependencies to ensure version synchronization
- **Ve
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