Taiga MCP Server
Enables seamless integration between Large Language Models and Taiga project management platform, allowing users to manage projects, user stories, tasks, and team collaboration through natural language commands.
README
Taiga MCP Server
<div align="center">
A production-ready Model Context Protocol (MCP) server for Taiga Project Management
Getting Started • Features • Tools • Architecture • Contributing
</div>
📋 Overview
Taiga MCP Server enables seamless integration between Large Language Models (LLMs) and Taiga project management platform through the Model Context Protocol. Built with Python's async/await patterns and type-safe Pydantic models, it provides a robust, production-ready solution for AI-powered project management automation.
Why Taiga MCP?
- 🤖 Natural Language Interface: Interact with Taiga using conversational commands
- 🔄 Async-First: Built on modern async/await for high performance
- 🛡️ Type-Safe: Full Pydantic validation for reliability
- 🎯 Production Ready: Comprehensive error handling and logging
- 🔌 Extensible: Clean architecture for easy feature additions
- 📦 Zero Config: Works out-of-the-box with Claude Desktop, Cursor, Windsurf
✨ Features
Core Capabilities
| Feature | Description |
|---|---|
| 🔐 Authentication | Token-based auth with automatic refresh |
| 📊 Project Management | List, view, and search projects by ID or slug |
| 📝 User Stories | Full CRUD operations with pagination support |
| ✅ Task Management | Create and organize tasks within stories |
| 👥 Team Collaboration | View members and assign work |
| 🏷️ Rich Metadata | Tags, story points, due dates, custom fields |
| 🔍 Flexible Queries | Support for IDs, slugs, and reference numbers (#42) |
Technical Features
- Async Architecture: Non-blocking I/O for optimal performance
- Smart Caching: Token management with auto-refresh
- Intelligent Pagination: Auto-fetch all or page-by-page
- Optimistic Locking: Version-based updates prevent conflicts
- Role-Based Points: Automatic detection and handling
- Flexible Identifiers: Use IDs, slugs, or #ref numbers interchangeably
🚀 Quick Start
Prerequisites
- Python: 3.10 or higher
- Taiga Account: taiga.io or self-hosted instance
- MCP Client: Claude Desktop, Cursor, Windsurf, or any MCP-compatible client
Installation
# Clone the repository
git clone https://github.com/yourusername/taiga-mcp.git
cd taiga-mcp
# Create virtual environment (or use conda)
python -m venv venv
source venv/bin/activate # Windows: venv\Scripts\activate
# Install with dev dependencies
pip install -e ".[dev]"
# Configure credentials
cp .env.example .env
nano .env # Add your Taiga credentials
Configuration
Create .env file:
TAIGA_API_URL=https://api.taiga.io/api/v1
TAIGA_USERNAME=your_username
TAIGA_PASSWORD=your_password
DEBUG=false
See RUN.md for detailed setup instructions for Claude Desktop and Claude Code.
🛠️ Available Tools
The server exposes 10 tools through the MCP protocol:
Authentication
| Tool | Description | Parameters |
|---|---|---|
authenticate |
Authenticate with Taiga API | username (optional), password (optional) |
Project Management
| Tool | Description | Parameters |
|---|---|---|
listProjects |
List all accessible projects | None |
getProject |
Get project details | projectIdentifier (ID or slug) |
listProjectMembers |
List project team members | projectIdentifier |
User Story Management
| Tool | Description | Parameters |
|---|---|---|
createUserStory |
Create a new user story | projectIdentifier, subject, description, status, tags* |
listUserStories |
List stories with pagination | projectIdentifier, pageSize, page, fetchAll* |
getUserStory |
Get story details | userStoryIdentifier, projectIdentifier* |
updateUserStory |
Update existing story | userStoryIdentifier, projectIdentifier, subject, description, status, assignedTo, tags, points, dueDate |
Task Management
| Tool | Description | Parameters |
|---|---|---|
createTask |
Create task in story | projectIdentifier, userStoryIdentifier, subject, description, status, tags* |
listUserStoryTasks |
List tasks for a story | userStoryIdentifier, projectIdentifier* |
* = optional parameter
💬 Example Usage
Once configured with your LLM client, use natural language:
"List all my Taiga projects"
"Show me details about project 'mobile-app'"
"Create a user story in backend-api titled 'Implement OAuth2 authentication'
with description 'Add JWT-based OAuth2 flow for API endpoints'"
"List all user stories in the mobile-app project"
"Update user story #42 - set status to 'In Progress' and assign to john"
"Show me all tasks for user story #42"
"Create a task in story #42 titled 'Write unit tests for auth module'"
🏗️ Architecture
Tech Stack
| Component | Technology | Purpose |
|---|---|---|
| Protocol | MCP 1.0 | LLM-tool communication |
| Language | Python 3.10+ | Core implementation |
| HTTP Client | httpx | Async Taiga API calls |
| Validation | Pydantic v2 | Type-safe data models |
| Config | pydantic-settings | Environment management |
| Testing | pytest + pytest-asyncio | Test framework |
Project Structure
taiga-mcp/
├── app/ # Main application package
│ ├── core/ # Core functionality
│ │ ├── auth.py # Authentication & token management
│ │ ├── client.py # Async HTTP client wrapper
│ │ └── exceptions.py # Custom exception hierarchy
│ ├── models/ # Pydantic data models
│ │ ├── project.py # Project & member models
│ │ ├── userstory.py # User story models
│ │ ├── task.py # Task models
│ │ ├── user.py # User models
│ │ └── status.py # Status models
│ ├── services/ # Business logic layer
│ │ ├── project_service.py # Project operations
│ │ ├── userstory_service.py # User story operations
│ │ ├── task_service.py # Task operations
│ │ └── user_service.py # User operations
│ ├── config.py # Settings management
│ └── server.py # MCP server & tool definitions
├── tests/ # Test suite
│ ├── unit/ # Unit tests
│ └── integration/ # Integration tests
├── pyproject.toml # Project metadata & dependencies
├── README.md # This file
├── RUN.md # Setup & usage guide
└── .env.example # Example environment config
Design Patterns
1. Async/Await Throughout
All I/O operations use Python's async/await for non-blocking execution:
async with TaigaClient() as client:
projects = await project_service.list_projects()
2. Service Layer Pattern
Business logic is encapsulated in service classes:
class ProjectService:
async def list_projects(self) -> list[Project]:
data = await self.client.get("/projects")
return [Project(**proj) for proj in data]
3. Pydantic Validation
All data is validated using Pydantic models:
class UserStory(BaseModel):
id: int
subject: str
tags: list[str] = Field(default_factory=list)
@field_validator("tags", mode="before")
@classmethod
def normalize_tags(cls, v: Any) -> list[str]:
# Handle both ['tag'] and [['tag', None]] formats
...
4. Error Handling
Custom exception hierarchy for precise error handling:
try:
await client.get("/projects/123")
except ResourceNotFoundError as e:
logger.error(f"Project not found: {e.identifier}")
except TaigaAPIError as e:
logger.error(f"API error: {e.status_code}")
🔧 Development
Setup Development Environment
# Install with development dependencies
pip install -e ".[dev]"
# Run tests
pytest
# Run tests with coverage
pytest --cov=app --cov-report=html
# Format code
black app/ tests/
# Lint code
ruff check app/ tests/
# Type check
mypy app/
Running Tests
# All tests
pytest
# Specific test file
pytest tests/unit/test_auth.py -v
# Integration tests (requires Taiga credentials)
pytest tests/integration/ -v
# With coverage report
pytest --cov=app --cov-report=term-missing
Code Quality Tools
| Tool | Purpose | Command |
|---|---|---|
| Black | Code formatting | black app/ tests/ |
| Ruff | Fast linting | ruff check app/ tests/ |
| Mypy | Type checking | mypy app/ |
| Pytest | Testing | pytest |
🗺️ Roadmap
Phase 1: Core Features ✅
- [x] Authentication & token management
- [x] Project listing and details
- [x] User story CRUD operations
- [x] Task management
- [x] Team member listing
- [x] Smart pagination
- [x] Flexible identifiers (ID/slug/#ref)
Phase 2: Enhanced Features 🚧
- [ ] Caching layer (Redis/in-memory)
- [ ] Rate limiting
- [ ] Bulk operations
- [ ] Epic support
- [ ] Sprint/Milestone management
- [ ] Issues/Bugs tracking
- [ ] Wiki page integration
- [ ] File attachments
- [ ] Comments on stories/tasks
- [ ] Custom field support
- [ ] Activity history tracking
Phase 3: Advanced Features 🎯
- [ ] Standalone CLI tool
- [ ] Analytics & reporting
- [ ] Data export/import
- [ ] Webhook support
- [ ] Notification integrations (Slack, Email)
- [ ] Project templates
- [ ] Burndown charts
- [ ] Time tracking
🤝 Contributing
Contributions are welcome! Here's how to get started:
- Fork the repository
- Create a feature branch:
git checkout -b feature/amazing-feature - Make your changes
- Add tests: Ensure coverage for new code
- Run quality checks:
black app/ tests/ ruff check app/ tests/ mypy app/ pytest - Commit your changes:
git commit -m 'Add amazing feature' - Push to branch:
git push origin feature/amazing-feature - Open a Pull Request
Development Guidelines
- Follow existing code style (Black formatting)
- Add type hints to all functions
- Write docstrings for public APIs
- Include tests for new features
- Update documentation as needed
📝 License
This project is licensed under the The GNU General Public License v3.0 - see the LICENSE file for details.
🙏 Acknowledgments
- Model Context Protocol - For the excellent LLM-tool integration standard
- Taiga - For the powerful open-source project management platform
- Anthropic - For Claude and MCP SDK
- Community Contributors - For feedback and improvements
📞 Support
- Documentation: RUN.md for setup guides
- Issues: GitHub Issues
- Discussions: GitHub Discussions
- Taiga API Docs: https://docs.taiga.io/api.html
<div align="center">
Built with ❤️ for the AI-powered project management community
⭐ Star this repo if you find it useful!
</div>
⚠️ Disclaimer
This project is not officially affiliated with Taiga. It's a community-driven MCP server implementation for integrating Taiga with LLM applications.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。