What is the Yandex Tracker MCP server?

Yandex Tracker is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.

How do MCP servers relate to agent skills?

Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.

How are reviews shown for Yandex Tracker?

This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.

Yandex Tracker▌

by aikts

Integrate Yandex Tracker with project management software for advanced issue tracking, project plan templates, Gantt cha

Integrates with Yandex Tracker for comprehensive issue management, queue operations, user management, and project data access with OAuth 2.0 authentication and Redis caching support.

github stars

★ 49

GitHub npm

OAuth 2.0 authenticationOptional Redis caching for performanceFull Query Language support

best for

/ Teams using Yandex Tracker for project management
/ Automating issue tracking workflows
/ AI assistants helping with ticket management

capabilities

/ Create and update Yandex Tracker issues
/ Manage queues with pagination and metadata
/ Execute status transitions and workflow changes
/ Search issues using Yandex Tracker Query Language
/ Retrieve user account and organizational data
/ Access custom fields and project configurations

what it does

Connects AI assistants to Yandex Tracker for managing issues, queues, users, and projects. Provides full access to Yandex Tracker's API with OAuth authentication and optional Redis caching.

about

Yandex Tracker is a community-built MCP server published by aikts that provides AI assistants with tools and capabilities via the Model Context Protocol. Integrate Yandex Tracker with project management software for advanced issue tracking, project plan templates, Gantt cha

how to install

You can install Yandex Tracker in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

Apache-2.0

Yandex Tracker is released under the Apache-2.0 license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Yandex Tracker MCP Server

mcp-name: io.github.aikts/yandex-tracker-mcp

A comprehensive Model Context Protocol (MCP) server that enables AI assistants to interact with Yandex Tracker APIs. This server provides secure, authenticated access to Yandex Tracker issues, queues, comments, worklogs, and search functionality with optional Redis caching for improved performance.

Documentation in Russian is available here / Документация на русском языке доступна здесь.

Features

Complete Queue Management: List and access all available Yandex Tracker queues with pagination support, tag retrieval, and detailed metadata
User Management: Retrieve user account information, including login details, email addresses, license status, and organizational data
Full Issue Lifecycle: Create, read, update, and manage issues with support for custom fields, attachments, and workflow transitions
Status Workflow Management: Execute status transitions, close issues with resolutions, and navigate complex workflows
Field Management: Access global fields, queue-specific local fields, statuses, issue types, priorities, and resolutions
Advanced Query Language: Full Yandex Tracker Query Language support with complex filtering, sorting, and date functions
Performance Caching: Optional Redis caching layer for improved response times
Security Controls: Configurable queue access restrictions and secure token handling
Multiple Transport Options: Support for stdio, SSE (deprecated), and HTTP transports for flexible integration
OAuth 2.0 Authentication: Dynamic token-based authentication with automatic refresh support as an alternative to static API tokens
Organization Support: Compatible with both standard and cloud organization IDs

Organization ID Configuration

Choose one of the following based on your Yandex organization type:

Yandex Cloud Organization: Use TRACKER_CLOUD_ORG_ID env var later for Yandex Cloud-managed organizations
Yandex 360 Organization: Use TRACKER_ORG_ID env var later for Yandex 360 organizations

You can find your organization ID in the Yandex Tracker URL or organization settings.

MCP Client Configuration

Installing extension in Claude Desktop

Yandex Tracker MCP Server can be one-click installed in Claude Desktop as and extension.

Installation

Download the *.mcpb file from GitHub Releases.
Double-click the downloaded file to install it in Claude Desktop.
Provide your Yandex Tracker OAuth token when prompted.
Make sure extension is enabled - now you may use this MCP Server.

Manual installation

Prerequisites

uv installed globally
Valid Yandex Tracker API token with appropriate permissions

The following sections show how to configure the MCP server for different AI clients. You can use either uvx yandex-tracker-mcp@latest or the Docker image ghcr.io/aikts/yandex-tracker-mcp:latest. Both require these environment variables:

Authentication (one of the following):
- TRACKER_TOKEN - Your Yandex Tracker OAuth token
- TRACKER_IAM_TOKEN - Your IAM token
- TRACKER_SA_KEY_ID, TRACKER_SA_SERVICE_ACCOUNT_ID, TRACKER_SA_PRIVATE_KEY - Service account credentials
TRACKER_CLOUD_ORG_ID or TRACKER_ORG_ID - Your Yandex Cloud (or Yandex 360) organization ID

<details> <summary>Claude Desktop</summary>

Configuration file path:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

Using uvx:

{
  "mcpServers": {
    "yandex-tracker": {
      "command": "uvx",
      "args": ["yandex-tracker-mcp@latest"],
      "env": {
        "TRACKER_TOKEN": "your_tracker_token_here",
        "TRACKER_CLOUD_ORG_ID": "your_cloud_org_id_here",
        "TRACKER_ORG_ID": "your_org_id_here"
      }
    }
  }
}

Using Docker:

{
  "mcpServers": {
    "yandex-tracker": {
      "command": "docker",
      "args": [
        "run", "--rm", "-i",
        "-e", "TRACKER_TOKEN",
        "-e", "TRACKER_CLOUD_ORG_ID",
        "-e", "TRACKER_ORG_ID",
        "ghcr.io/aikts/yandex-tracker-mcp:latest"
      ],
      "env": {
        "TRACKER_TOKEN": "your_tracker_token_here",
        "TRACKER_CLOUD_ORG_ID": "your_cloud_org_id_here",
        "TRACKER_ORG_ID": "your_org_id_here"
      }
    }
  }
}

</details> <details> <summary>Claude Code</summary>

Using uvx:

claude mcp add yandex-tracker uvx yandex-tracker-mcp@latest \
  -e TRACKER_TOKEN=your_tracker_token_here \
  -e TRACKER_CLOUD_ORG_ID=your_cloud_org_id_here \
  -e TRACKER_ORG_ID=your_org_id_here \
  -e TRANSPORT=stdio

Using Docker:

claude mcp add yandex-tracker docker "run --rm -i -e TRACKER_TOKEN=your_tracker_token_here -e TRACKER_CLOUD_ORG_ID=your_cloud_org_id_here -e TRACKER_ORG_ID=your_org_id_here -e TRANSPORT=stdio ghcr.io/aikts/yandex-tracker-mcp:latest"

</details> <details> <summary>Cursor</summary>

Configuration file path:

Project-specific: .cursor/mcp.json in your project directory
Global: ~/.cursor/mcp.json

Using uvx:

{
  "mcpServers": {
    "yandex-tracker": {
      "command": "uvx",
      "args": ["yandex-tracker-mcp@latest"],
      "env": {
        "TRACKER_TOKEN": "your_tracker_token_here",
        "TRACKER_CLOUD_ORG_ID": "your_cloud_org_id_here",
        "TRACKER_ORG_ID": "your_org_id_here"
      }
    }
  }
}

Using Docker:

{
  "mcpServers": {
    "yandex-tracker": {
      "command": "docker",
      "args": [
        "run", "--rm", "-i",
        "-e", "TRACKER_TOKEN",
        "-e", "TRACKER_CLOUD_ORG_ID",
        "-e", "TRACKER_ORG_ID",
        "ghcr.io/aikts/yandex-tracker-mcp:latest"
      ],
      "env": {
        "TRACKER_TOKEN": "your_tracker_token_here",
        "TRACKER_CLOUD_ORG_ID": "your_cloud_org_id_here",
        "TRACKER_ORG_ID": "your_org_id_here"
      }
    }
  }
}

</details> <details> <summary>Windsurf</summary>

Configuration file path:

~/.codeium/windsurf/mcp_config.json

Access via: Windsurf Settings → Cascade tab → Model Context Protocol (MCP) Servers → "View raw config"

Using uvx:

{
  "mcpServers": {
    "yandex-tracker": {
      "command": "uvx",
      "args": ["yandex-tracker-mcp@latest"],
      "env": {
        "TRACKER_TOKEN": "your_tracker_token_here",
        "TRACKER_CLOUD_ORG_ID": "your_cloud_org_id_here",
        "TRACKER_ORG_ID": "your_org_id_here"
      }
    }
  }
}

Using Docker:

{
  "mcpServers": {
    "yandex-tracker": {
      "command": "docker",
      "args": [
        "run", "--rm", "-i",
        "-e", "TRACKER_TOKEN",
        "-e", "TRACKER_CLOUD_ORG_ID",
        "-e", "TRACKER_ORG_ID",
        "ghcr.io/aikts/yandex-tracker-mcp:latest"
      ],
      "env": {
        "TRACKER_TOKEN": "your_tracker_token_here",
        "TRACKER_CLOUD_ORG_ID": "your_cloud_org_id_here",
        "TRACKER_ORG_ID": "your_org_id_here"
      }
    }
  }
}

</details> <details> <summary>Zed</summary>

Configuration file path:

~/.config/zed/settings.json

Access via: Cmd+, (macOS) or Ctrl+, (Linux/Windows) or command palette: "zed: open settings"

Note: Requires Zed Preview version for MCP support.

Using uvx:

{
  "context_servers": {
    "yandex-tracker": {
      "source": "custom",
      "command": {
        "path": "uvx",
        "args": ["yandex-tracker-mcp@latest"],
        "env": {
          "TRACKER_TOKEN": "your_tracker_token_here",
          "TRACKER_CLOUD_ORG_ID": "your_cloud_org_id_here",
          "TRACKER_ORG_ID": "your_org_id_here"
        }
      }
    }
  }
}

Using Docker:

{
  "context_servers": {
    "yandex-tracker": {
      "source": "custom",
      "command": {
        "path": "docker",
        "args": [
          "run", "--rm", "-i",
          "-e", "TRACKER_TOKEN",
          "-e", "TRACKER_CLOUD_ORG_ID",
          "-e", "TRACKER_ORG_ID",
          "ghcr.io/aikts/yandex-tracker-mcp:latest"
        ],
        "env": {
          "TRACKER_TOKEN": "your_tracker_token_here",
          "TRACKER_CLOUD_ORG_ID": "your_cloud_org_id_here",
          "TRACKER_ORG_ID": "your_org_id_here"
        }
      }
    }
  }
}

</details> <details> <summary>GitHub Copilot (VS Code)</summary>

Configuration file path:

Workspace: .vscode/mcp.json in your project directory
Global: VS Code settings.json

Option 1: Workspace Configuration (Recommended for security)

Create .vscode/mcp.json:

Using uvx:

{
  "inputs": [
    {
      "type": "promptString",
      "id": "tracker-token",
      "description": "Yandex Tracker Token",
      "password": true
    },
    {
      "type": "promptString",
      "id": "cloud-org-id",
      "description": "Yandex Cloud Organization ID"
    },
    {
      "type": "promptString",
      "id": "org-id",
      "description": "Yandex Tracker Organization ID (optional)"
    }
  ],
  "servers": {
    "yandex-tracker": {
      "type": "stdio",
      "command": "uvx",
      "args": ["yandex-tracker-mcp@latest"],
      "env": {
        "TRA

---

FAQ

What is the Yandex Tracker MCP server?: Yandex Tracker is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?: Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Yandex Tracker?: This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.

MCP server reviews

Ratings

4.5★★★★★10 reviews

★★★★★Shikha Mishra· Oct 10, 2024
Yandex Tracker is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
★★★★★Piyush G· Sep 9, 2024
We evaluated Yandex Tracker against two servers with overlapping tools; this profile had the clearer scope statement.
★★★★★Chaitanya Patil· Aug 8, 2024
Useful MCP listing: Yandex Tracker is the kind of server we cite when onboarding engineers to host + tool permissions.
★★★★★Sakshi Patil· Jul 7, 2024
Yandex Tracker reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
★★★★★Ganesh Mohane· Jun 6, 2024
I recommend Yandex Tracker for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
★★★★★Oshnikdeep· May 5, 2024
Strong directory entry: Yandex Tracker surfaces stars and publisher context so we could sanity-check maintenance before adopting.
★★★★★Dhruvi Jain· Apr 4, 2024
Yandex Tracker has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
★★★★★Rahul Santra· Mar 3, 2024
According to our notes, Yandex Tracker benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
★★★★★Pratham Ware· Feb 2, 2024
We wired Yandex Tracker into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
★★★★★Yash Thakker· Jan 1, 2024
Yandex Tracker is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.