talhaorak/pytaiga-mcp 的社区分支，包含额外功能、CI/CD 和持续维护。

概述

Taiga MCP 桥是一个强大的集成层，连接了 Taiga 项目管理平台与模型上下文协议（MCP），使 AI 工具和工作流程能够无缝与 Taiga 的资源交互。

该桥梁为人工智能代理提供了全面的工具和资源：

• 在 Taiga 中创建和管理项目、史诗、用户故事、任务和问题
• 田径短跑和里程碑
• 分配和更新工作项目
• 查询关于项目工件的详细信息
• 管理项目成员和权限

通过使用 MCP 标准，该桥梁使 AI 系统能够保持对项目状态的上下文感知，并以程序方式执行复杂的项目管理任务。

特色

综合资源支持

该桥支持以下塔伊加资源，提供完整的CRUD操作：

• 项目：创建、更新和管理项目设置及元数据
• 史诗级事件：管理跨多个冲刺的大型功能
• 用户故事：处理详细需求和验收标准

Taiga MCP Bridge

Community fork of talhaorak/pytaiga-mcp with additional features, CI/CD, and ongoing maintenance.

Overview

The Taiga MCP Bridge is a powerful integration layer that connects Taiga project management platform with the Model Context Protocol (MCP), enabling AI tools and workflows to interact seamlessly with Taiga’s resources.

This bridge provides a comprehensive set of tools and resources for AI agents to:

• Create and manage projects, epics, user stories, tasks, and issues in Taiga
• Track sprints and milestones
• Assign and update work items
• Query detailed information about project artifacts
• Manage project members and permissions

By using the MCP standard, this bridge allows AI systems to maintain contextual awareness about project state and perform complex project management tasks programmatically.

Features

Comprehensive Resource Support

The bridge supports the following Taiga resources with complete CRUD operations:

• Projects: Create, update, and manage project settings and metadata
• Epics: Manage large features that span multiple sprints
• User Stories: Handle detailed requirements and acceptance criteria
• Tasks: Track smaller units of work within user stories
• Issues: Manage bugs, questions, and enhancement requests
• Sprints (Milestones): Plan and track work in time-boxed intervals

Security & Configuration

• Secure Credentials: Environment variable authentication with credential protection - passwords never appear in logs or error messages
• Auto-Authentication: Configure TAIGA_USERNAME and TAIGA_PASSWORD environment variables for seamless startup without manual login
• Input Validation: Allowlist-based parameter validation prevents unexpected data from reaching the Taiga API

Response Filtering

All tools support a verbosity parameter to control response size, reducing AI context usage:

Example:

# Get minimal response for efficient context usage
stories = client.call_tool("list_user_stories", {
    "project_id": 123,
    "verbosity": "minimal"
})