"Buy Me A Coffee" matching MCP servers:

Enables coding agents to query the dependency graph of a GitHub backlog, retrieve ordered ready work and prerequisite chains, atomically claim issues, and report blockers—so agents work in the correct order and safely in parallel.

Comprehensive quest orchestration system with KĀDI broker integration, multi-channel approval workflow, and Git-backed data storage.

A deterministic MCP server that reimplements ai-git-fish workflows (aicommit, aibranch, aipr) with Leantime integration, enabling Claude Code and Codex to perform git operations and manage tickets without an internal LLM.

AI 規格大師 — MCP server bridging specs (Linear / JIRA / GitHub Issues / Notion / Markdown / Figma) to tests, with bidirectional traceability and a spec-quality coach. Sibling to mk-qa-master.

Exposes a Notion-synced AI OS as read-only MCP tools, enabling MCP-compatible AI clients to search the vault, fetch page contents, list projects, and check project statuses without scraping public links.

A shared coordination layer for multiple AI coding assistants, exposing a persistent task queue, per-task message threads, and progress tracking via JSON files on disk.

A local-first MCP server that handles daily work tasks through your AI assistant: converts meeting notes into todos, manages todo lifecycle, tracks work hours, generates daily/weekly reports, organizes files via move-only operations, and diagnoses dev environments, all guarded by a human-maintained preview/apply safety model.

Small MCP server for connecting to enterprise Jira using a personal access token. It enables issue operations, project listing, JQL searches, and attachment handling.

A production-ready MCP server that connects AI assistants to the D-Tools System Integrator platform, enabling natural language management of AV projects, clients, catalogs, tasks, service orders, and purchase orders.

A Korean-centric MCP server for storing code review results and managing tasks, integrating with LLMs like Claude for review generation.

Enables autonomous AI-to-AI collaboration between Claude and Gemini to execute complex development projects with minimal human intervention. It provides a role-based system with task dependencies, automated project planning, and continuous execution loops.

A Model Context Protocol (MCP) server that enables AI clients to read and manage your Planka boards using the Planka REST API.

Connects AI assistants to SE Ranking's SEO and project management APIs to enable natural language queries for keyword research, backlink analysis, and technical audits. It supports comprehensive tasks including competitive analysis, domain traffic tracking, and AI search visibility monitoring.

Enables AI agents to manage Kanban boards, cards, sessions, and automations through a unified MCP interface with real-time updates, supporting delegation, agent sessions, and human-in-the-loop interactions.

Enforces engineering governance for AI-driven software projects, ensuring state over prompt, freeze over generate, and audit over output through the 5S workflow.

Enables AI agents to manage tasks through a structured lifecycle (todo, in_progress, ai_testing, manual_testing, deployment, completed) with human approval gates, providing a single-user task management system with CLI, REST API, and live updates.

Provides AI assistants with a standardized interface to interact with the Todo for AI task management system. It enables users to retrieve project tasks, create new entries, and submit completion feedback through natural language.

MCP server for Redmine that enables interaction with issues, wiki pages, and time entries through natural language.

MCP server that enables AI agents to access and modify Todoist tasks, such as finding tasks by date and adding tasks, via natural language.

A zero-dependency MCP server that answers common questions about Jira work, such as what is assigned to me, standup status, sprint health, and more, without returning raw issue JSON.