yandex-tracker-mcp
Verified Safeby aikts
Overview
This server acts as a Model Context Protocol (MCP) interface, enabling AI assistants to securely interact with the Yandex Tracker API for managing issues, queues, users, and various other project management functionalities.
Installation
python -m mcp_trackerEnvironment Variables
- TRACKER_TOKEN
- TRACKER_IAM_TOKEN
- TRACKER_SA_KEY_ID
- TRACKER_SA_SERVICE_ACCOUNT_ID
- TRACKER_SA_PRIVATE_KEY
- TRACKER_CLOUD_ORG_ID
- TRACKER_ORG_ID
- OAUTH_ENABLED
- OAUTH_CLIENT_ID
- OAUTH_CLIENT_SECRET
- MCP_SERVER_PUBLIC_URL
Security Notes
The server primarily relies on environment variables for sensitive data (tokens, client secrets), which is good practice. It supports various authentication methods including OAuth 2.0 with PKCE for enhanced security. However, when configured for OAuth, the server explicitly requires a publicly accessible URL for callbacks, which introduces a network exposure point that must be properly secured. Redis caching, if enabled, also requires a secure Redis instance. Overall, robust authentication mechanisms are in place, but network exposure in HTTP/OAuth modes requires careful deployment.
Similar Servers
mcphub
A hub for managing, orchestrating, and providing a unified API for various Model Context Protocol (MCP) servers and their tools, including user management, OAuth services, and discovery of external servers.
tmcp
Build Model Context Protocol (MCP) servers for AI agents, providing schema-agnostic tools, resources, and prompts, with optional OAuth 2.1 authentication and distributed session management.
backlog-mcp-server
Integrate Backlog API with AI agents (e.g., Claude) to manage projects, issues, wikis, and Git repositories through natural language commands.
mcp-servers
Provides a curated collection of Model Context Protocol (MCP) server configurations to enable AI agents to interact with various developer tools and services.