"Keep a Changelog" matching MCP servers:

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.

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.

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.

This server enables GitHub issue triage with three focused tools: searching issues, summarizing an issue with recent comments, and drafting comments with dry-run/gated posting, using shaped payloads and retries to keep context small.

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 agents to keep Linear tickets current by treating the description as the ticket's state and comments as its log, with validated section patches, reconciled drift reporting, whole-ticket reads, typed comments, and a hash-checked claim-then-Done gate. Enforces these rules server-side so they hold across any client, including hands-off labels and refusal of stale or unverified writes.

Integrates Google Calendar and Notion to enable Claude to manage your schedule, plan tasks, detect conflicts, and keep appointments and tasks synchronized.

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.

Enables GitHub project management from Claude, supporting issue creation, milestones, labels, changelog generation, and repository stats.

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.

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.

Enables recording estimates, slices, intervals, and absences for work efforts, and later analyzing them to calibrate estimation accuracy by comparing initial and final estimates against actual wall time, while hiding duration data during estimation to keep estimates unbiased.

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.