# AceFlow MCP Server
AI-driven workflow management through Model Context Protocol.
## 📁 Project Structure
```
aceflow-mcp-server/
├── aceflow_mcp_server/ # Core package directory
│ ├── core/ # Core functionality modules
│ ├── main.py # Main entry point
│ ├── tools.py # Tool implementations
│ └── ...
├── tests/ # Formal test suite
├── examples/ # Examples and demo code
├── scripts/ # Build and deployment scripts
│ ├── build/ # Build-related scripts
│ ├── deploy/ # Deployment scripts
│ └── dev/ # Development tools
├── docs/ # Documentation
│ ├── user-guide/ # User guides
│ ├── developer-guide/ # Developer guides
│ └── project/ # Project documentation
├── dev-tests/ # Development tests and experiments
└── pyproject.toml # Project configuration
```
## Overview
AceFlow MCP Server provides structured software development workflows through the Model Context Protocol (MCP), enabling AI clients like Kiro, Cursor, and Claude to manage projects with standardized processes.
## Features
### 🛠️ MCP Tools
- **aceflow_init**: Initialize projects with different workflow modes
- **aceflow_stage**: Manage project stages and workflow progression
- **aceflow_validate**: Validate project compliance and quality
- **aceflow_template**: Manage workflow templates
### 📊 MCP Resources
- **aceflow://project/state**: Current project state and progress
- **aceflow://workflow/config**: Workflow configuration and settings
- **aceflow://stage/guide/{stage}**: Stage-specific guidance and instructions
### 🤖 MCP Prompts
- **workflow_assistant**: Context-aware workflow guidance
- **stage_guide**: Stage-specific assistance and best practices
## Quick Start
### Installation
```bash
# Method 1: Install via uvx (recommended for end users)
uvx aceflow-mcp-server
# Method 2: Install via pip (traditional method)
pip install aceflow-mcp-server
# Method 3: Install with optional features
pip install aceflow-mcp-server[performance,monitoring]
```
### MCP Client Configuration
#### For uvx installation:
```json
{
"mcpServers": {
"aceflow": {
"command": "uvx",
"args": ["aceflow-mcp-server@latest"],
"env": {
"ACEFLOW_LOG_LEVEL": "INFO"
}
}
}
}
```
#### For pip installation:
```json
{
"mcpServers": {
"aceflow": {
"command": "aceflow-mcp-server",
"args": [],
"env": {
"ACEFLOW_LOG_LEVEL": "INFO"
}
}
}
}
```
### Usage Example
```
User: "I want to start a new AI project with standard workflow"
AI: I'll help you initialize a new project using AceFlow.
[Uses aceflow_init tool]
✅ Project initialized successfully in standard mode!
Current status:
- Project: ai-project
- Mode: STANDARD
- Stage: user_stories (0% complete)
Ready to begin with user story analysis. Would you like guidance for this stage?
```
## Workflow Modes
### Minimal Mode
Fast prototyping and concept validation
- 3 stages: Implementation → Test → Demo
- Ideal for MVPs and quick experiments
### Standard Mode
Traditional software development workflow
- 8 stages: User Stories → Task Breakdown → Test Design → Implementation → Unit Test → Integration Test → Code Review → Demo
- Balanced approach for most projects
### Complete Mode
Enterprise-grade development process
- 12 stages: Full requirements analysis through security review
- Comprehensive quality gates and documentation
### Smart Mode
AI-enhanced adaptive workflow
- 10 stages with intelligent adaptation
- Dynamic complexity assessment and optimization
## Architecture
```
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ AI Client │ │ MCP Server │ │ AceFlow Core │
│ (Kiro/Cursor) │◄──►│ (FastMCP) │◄──►│ Engine │
└─────────────────┘ └─────────────────┘ └─────────────────┘
│
▼
┌─────────────────┐
│ File System │
│ (.aceflow/...) │
└─────────────────┘
```
## Development
### Setup
```bash
# Clone repository
git clone https://github.com/aceflow/aceflow-mcp-server
cd aceflow-mcp-server
# Install development dependencies
pip install -e ".[dev]"
# Run tests
pytest
# Run with coverage
pytest --cov=aceflow_mcp_server
```
### Project Structure
```
aceflow-mcp-server/
├── aceflow_mcp_server/
│ ├── __init__.py
│ ├── server.py # Main MCP server
│ ├── tools.py # MCP tools implementation
│ ├── resources.py # MCP resources
│ ├── prompts.py # MCP prompts
│ └── core/ # Core functionality
├── tests/ # Test suite
├── docs/ # Documentation
└── pyproject.toml # Project configuration
```
## Contributing
1. Fork the repository
2. Create a feature branch
3. Add tests for new functionality
4. Ensure all tests pass
5. Submit a pull request
## License
MIT License - see LICENSE file for details.
## Support
- **Documentation**: https://docs.aceflow.dev/mcp
- **Issues**: https://github.com/aceflow/aceflow-mcp-server/issues
- **Discussions**: https://github.com/aceflow/aceflow-mcp-server/discussions
---
*Generated by AceFlow v3.0 MCP Server*
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"description": "# AceFlow MCP Server\n\nAI-driven workflow management through Model Context Protocol.\n\n## \ud83d\udcc1 Project Structure\n\n```\naceflow-mcp-server/\n\u251c\u2500\u2500 aceflow_mcp_server/ # Core package directory\n\u2502 \u251c\u2500\u2500 core/ # Core functionality modules\n\u2502 \u251c\u2500\u2500 main.py # Main entry point\n\u2502 \u251c\u2500\u2500 tools.py # Tool implementations\n\u2502 \u2514\u2500\u2500 ...\n\u251c\u2500\u2500 tests/ # Formal test suite\n\u251c\u2500\u2500 examples/ # Examples and demo code\n\u251c\u2500\u2500 scripts/ # Build and deployment scripts\n\u2502 \u251c\u2500\u2500 build/ # Build-related scripts\n\u2502 \u251c\u2500\u2500 deploy/ # Deployment scripts\n\u2502 \u2514\u2500\u2500 dev/ # Development tools\n\u251c\u2500\u2500 docs/ # Documentation\n\u2502 \u251c\u2500\u2500 user-guide/ # User guides\n\u2502 \u251c\u2500\u2500 developer-guide/ # Developer guides\n\u2502 \u2514\u2500\u2500 project/ # Project documentation\n\u251c\u2500\u2500 dev-tests/ # Development tests and experiments\n\u2514\u2500\u2500 pyproject.toml # Project configuration\n```\n\n## Overview\n\nAceFlow MCP Server provides structured software development workflows through the Model Context Protocol (MCP), enabling AI clients like Kiro, Cursor, and Claude to manage projects with standardized processes.\n\n## Features\n\n### \ud83d\udee0\ufe0f MCP Tools\n- **aceflow_init**: Initialize projects with different workflow modes\n- **aceflow_stage**: Manage project stages and workflow progression \n- **aceflow_validate**: Validate project compliance and quality\n- **aceflow_template**: Manage workflow templates\n\n### \ud83d\udcca MCP Resources\n- **aceflow://project/state**: Current project state and progress\n- **aceflow://workflow/config**: Workflow configuration and settings\n- **aceflow://stage/guide/{stage}**: Stage-specific guidance and instructions\n\n### \ud83e\udd16 MCP Prompts\n- **workflow_assistant**: Context-aware workflow guidance\n- **stage_guide**: Stage-specific assistance and best practices\n\n## Quick Start\n\n### Installation\n\n```bash\n# Method 1: Install via uvx (recommended for end users)\nuvx aceflow-mcp-server\n\n# Method 2: Install via pip (traditional method)\npip install aceflow-mcp-server\n\n# Method 3: Install with optional features\npip install aceflow-mcp-server[performance,monitoring]\n```\n\n### MCP Client Configuration\n\n#### For uvx installation:\n```json\n{\n \"mcpServers\": {\n \"aceflow\": {\n \"command\": \"uvx\",\n \"args\": [\"aceflow-mcp-server@latest\"],\n \"env\": {\n \"ACEFLOW_LOG_LEVEL\": \"INFO\"\n }\n }\n }\n}\n```\n\n#### For pip installation:\n```json\n{\n \"mcpServers\": {\n \"aceflow\": {\n \"command\": \"aceflow-mcp-server\",\n \"args\": [],\n \"env\": {\n \"ACEFLOW_LOG_LEVEL\": \"INFO\"\n }\n }\n }\n}\n```\n\n### Usage Example\n\n```\nUser: \"I want to start a new AI project with standard workflow\"\n\nAI: I'll help you initialize a new project using AceFlow.\n\n[Uses aceflow_init tool]\n\u2705 Project initialized successfully in standard mode!\n\nCurrent status:\n- Project: ai-project\n- Mode: STANDARD\n- Stage: user_stories (0% complete)\n\nReady to begin with user story analysis. Would you like guidance for this stage?\n```\n\n## Workflow Modes\n\n### Minimal Mode\nFast prototyping and concept validation\n- 3 stages: Implementation \u2192 Test \u2192 Demo\n- Ideal for MVPs and quick experiments\n\n### Standard Mode \nTraditional software development workflow\n- 8 stages: User Stories \u2192 Task Breakdown \u2192 Test Design \u2192 Implementation \u2192 Unit Test \u2192 Integration Test \u2192 Code Review \u2192 Demo\n- Balanced approach for most projects\n\n### Complete Mode\nEnterprise-grade development process\n- 12 stages: Full requirements analysis through security review\n- Comprehensive quality gates and documentation\n\n### Smart Mode\nAI-enhanced adaptive workflow\n- 10 stages with intelligent adaptation\n- Dynamic complexity assessment and optimization\n\n## Architecture\n\n```\n\u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2510 \u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2510 \u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2510\n\u2502 AI Client \u2502 \u2502 MCP Server \u2502 \u2502 AceFlow Core \u2502\n\u2502 (Kiro/Cursor) \u2502\u25c4\u2500\u2500\u25ba\u2502 (FastMCP) \u2502\u25c4\u2500\u2500\u25ba\u2502 Engine \u2502\n\u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518 \u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518 \u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518\n \u2502\n \u25bc\n \u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2510\n \u2502 File System \u2502\n \u2502 (.aceflow/...) \u2502\n \u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518\n```\n\n## Development\n\n### Setup\n\n```bash\n# Clone repository\ngit clone https://github.com/aceflow/aceflow-mcp-server\ncd aceflow-mcp-server\n\n# Install development dependencies\npip install -e \".[dev]\"\n\n# Run tests\npytest\n\n# Run with coverage\npytest --cov=aceflow_mcp_server\n```\n\n### Project Structure\n\n```\naceflow-mcp-server/\n\u251c\u2500\u2500 aceflow_mcp_server/\n\u2502 \u251c\u2500\u2500 __init__.py\n\u2502 \u251c\u2500\u2500 server.py # Main MCP server\n\u2502 \u251c\u2500\u2500 tools.py # MCP tools implementation\n\u2502 \u251c\u2500\u2500 resources.py # MCP resources\n\u2502 \u251c\u2500\u2500 prompts.py # MCP prompts\n\u2502 \u2514\u2500\u2500 core/ # Core functionality\n\u251c\u2500\u2500 tests/ # Test suite\n\u251c\u2500\u2500 docs/ # Documentation\n\u2514\u2500\u2500 pyproject.toml # Project configuration\n```\n\n## Contributing\n\n1. 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