Yandex Tracker MCP, developed by Aikts, is a Python-based server tool designed to connect AI assistants with Yandex Tracker APIs. This free Model Context Protocol server enables secure, authenticated access to Yandex Tracker issues, queues, comments, worklogs, and search functions. It supports distribution as a Python package, a Docker image, or an .mcpb file for Claude Desktop. Yandex Tracker MCP is categorized as both an MCP server and Developer Tools, offering a powerful bridge for enhancing productivity through AI-driven workflows.

What does Yandex Tracker MCP connect to?

The Yandex Tracker MCP server links directly to Yandex Tracker APIs. It provides secure, authenticated access to key Yandex Tracker entities, including issues, queues, comments, worklogs, and search capabilities. This connection positions it as a vital component for integrating AI assistants into project and task management within the Yandex ecosystem. It is specifically designed as a Model Context Protocol server and a developer tool, facilitating advanced interactions with the Yandex Tracker platform.

Core features and tools

The server exposes several callable tools, such as queues_get_all to list all available queues, queue_get_tags for queue-specific tags, queue_get_versions for queue versions, queue_get_fields for queue fields, and queue_get_metadata for detailed queue information. Beyond these, it supports full queue management, projects, portfolios, goals (including project_add_checklist_item), user management, the entire issue lifecycle (create, read, update, manage), status workflow management, field management, boards and sprints, and advanced query language support.

Who is it for?

Yandex Tracker MCP is intended for developers and project managers who seek to integrate AI assistants with the Yandex Tracker platform. Its capabilities are suitable for various teams, including marketing, human resources, software development, document flow, procurement, support, and design, aiming to boost productivity. Skip this if you do not use Yandex Tracker for project or issue management.

How to get started

Access is granted through a standard OAuth authorization flow, or via static tokens and service account credentials. It supports HTTP transport protocols. Setting the OAUTH_ENABLED environment variable to true, along with client ID and secret, is required for OAuth 2.0.

Use cases

• Automated Issue Management: AI assistants can create, read, update, and manage issues, including custom fields, attachments, and workflow transitions, as well as execute status transitions and close issues with resolutions.
• Enhanced Project Tracking: AI can list and access Yandex Tracker queues, manage projects, portfolios, and goals, and retrieve user account information for oversight.
• AI-powered Reporting and Analytics: AI can use the Yandex Tracker Query Language for filtering and sorting to generate reports, analyze work, statuses, and evaluations, and save progress reports as comments.

Yandex Tracker MCP offers a powerful way to connect AI assistants with Yandex Tracker, providing extensive control over project and issue management. Its flexible authentication and transport options make it adaptable for various integration needs across different teams. The tool is designed to enhance productivity by automating tasks and enabling AI-driven insights.