"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.

Enables persistent, auditable business operations state by storing knowledge, evidence, decisions, tasks, execution receipts, and review results in a local SQLite database, so different sessions can continue the same project.

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.

Enables answering 'what needs me right now?' across GitHub issues by determining whose turn it is and returning ready-to-read Markdown reports.

Connects Claude to Jobber to manage clients, jobs, invoices, quotes, and scheduling through natural language.

Enables multiple AI agents and humans working in the same project to share status, exchange messages, and claim files through a local collaboration board. It supports project-specific enablement, conflict-aware file claims, and shared state via SQLite.

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.

Enables multiple agents to file, label, comment on, and close issues in a shared git-bug store while the git-bug web UI remains open, with rule enforcement and safe concurrent writes.

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.

Connects AI assistants to the Basecamp 2 API, enabling management of projects, todos, messages, and people directly through natural language.

Exposes 105 MCP tools that let Claude and ChatGPT read and analyse a Mizito workspace's chats, projects, tasks, calendar, letters, minutes, surveys, notes and files (including PDF, Word, Excel and image content). Write, CRM and admin tools can optionally be enabled so the assistant can also send messages and letters, create and repeat tasks, manage kanban boards, and handle customer records.

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.

This read-only MCP Server allows you to connect to Jira data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

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.

Enables AI hosts to preserve and resume task and project state across conversations, process restarts, and worker or model replacement by storing structured records, snapshots, receipts, and bounded context views through a local stdio interface.

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.

Plans domestic jobs around your available hours by scheduling work and unavoidable waiting, then tracks progress and reschedules as conditions change. It answers deadline questions honestly, suggests what to buy, and tells you the next thing to do.

Enables AI agents to interact with GitLab repositories, allowing them to manage merge requests and issues including listing projects, fetching MR details and diffs, adding comments, and updating MR titles and descriptions.

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