"Yandex Cloud" matching MCP servers:

Enables AI assistants to securely interact with Yandex Tracker, managing issues, queues, comments, worklogs, and search, including attaching files to issues.

This MCP enables access to Yandex Tracker issue management. Currently it supports all read operations to retrieve queues, issues and users from Yandex Tracker.

A Model Context Protocol server that enables AI assistants to securely interact with Yandex Tracker, supporting issues, queues, comments, worklogs, search, and workflow management with optional Redis caching.

Enables AI assistants to read and manage issues, comments, checklists, worklogs, queues, users, metadata, and time reports through the Yandex Tracker REST API v3, requiring user confirmation before data-changing operations.

Enables AI assistants to securely interact with Yandex Tracker, covering queues, issues, comments, worklogs, checklists, boards, sprints, attachments, and advanced query-language search. Supports OAuth 2.0 or static token authentication, optional Redis caching, and stdio, SSE, or HTTP transports.

MCP server for Yandex Tracker API, enabling AI assistants to search, read, create, and edit issues, as well as manage comments, attachments, and links in Yandex Tracker.

A Node.js MCP server that enables AI assistants to interact with Yandex Tracker task management system through a standardized protocol, supporting operations like creating, updating, and searching issues.

Enables LLM agents to interact with Yandex Tracker (and future Yandex services) using per-user credentials instead of a shared org-wide token, supporting both single-user and multi-user modes.

Enables creating Jira issues and listing issue types for a Jira Cloud project using Basic Auth credentials.

Enables logging time entries to Jira Cloud issues, including adding worklogs, listing existing entries, and verifying credentials.

Tracks workflows, tasks, blockers, and decisions locally for Claude Code, using PGlite with no cloud dependencies.

An unofficial MCP server that enables AI assistants to work with Yandex Tracker, Yandex Mail, and Yandex Calendar on the user's behalf, supporting reading, writing, and workflow automations such as meeting follow-ups, standups, and email-to-task creation.

A read-only MCP server that bridges AI assistants to SAP Cloud ALM, exposing read APIs through four intent-based tools. It runs locally over stdio or remotely over Streamable HTTP, and can be deployed to SAP BTP Cloud Foundry.

Exposes Yandex Tracker's REST API v3 as tools for LLM clients, enabling issue management and queue operations via natural language.

Enables LLMs to interact with Jira Cloud through the official REST API v3, supporting operations like creating issues, searching with JQL, fetching issue details, and managing transitions.

Enables AI agents to interact with Jira Cloud, including listing boards and issues, adding comments, and searching users.

MCP server for JIRA Cloud REST API v3, enabling issue search, creation, updates, comments, and transitions.

Enables AI assistants to manage CRM deals and tasks on Aspro Cloud, including CRUD operations on deals, tasks, users, pipelines, and workflows.

MCP server that gives AI agents read/write access to your Things3 tasks via the Things API.

MCP server for Yandex Tracker API that provides 146 tools for managing issues, projects, boards, sprints, worklog and more.