"Integrating Confluence with AI Features like Search and Summarization" matching MCP servers:

Enables AI assistants to search, retrieve, and manage Confluence pages, and generate weekly status drafts from Jira activity.

Enables AI assistants to interact with Atlassian Confluence Cloud by providing tools to create, update, search, and delete pages. It facilitates seamless content management within Confluence spaces using Markdown and the Confluence REST API.

jira, wiki mcp

A Model Context Protocol server that integrates with Atlassian's Jira and Confluence, enabling AI assistants to interact with these tools directly through features like issue management, page creation, and content search.

This MCP server provides unified read/write access to Jira Cloud tickets and Confluence Cloud pages, enabling search, retrieval, and updates. It automatically downloads log attachments from tickets into a shared directory for the companion Log Intelligence MCP to ingest.

A Model Context Protocol server for Atlassian Jira and Confluence that bypasses corporate proxies and self-signed certificates, enabling read/write operations on issues, projects, pages, and spaces using Personal Access Tokens.

A Model Context Protocol (MCP) server that connects AI assistants to Jira and Confluence, enabling search, create, update, and comment operations with rich Markdown-to-ADF conversion.

Enables interaction with Jira and Confluence APIs to search, create, and manage issues, pages, comments, and attachments across both Atlassian platforms.

Enables async-first working practices by providing tools to draft decision docs, convert meetings to async artifacts, score status updates, and triage sync vs async tasks. It also offers reference tools for the Open and Async book's principles and coaching prompts.

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

MCP server enabling AI agents to interact with OpenProject API v3 for project management, including creating and managing work packages, projects, comments, time entries, boards, and user dashboards.

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.

Enables teams to measure their actual ticket-writing style from GitLab, Jira, or GitHub and check new or draft tickets against that learned house profile, with optional model-backed drafting.

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.

Enables AI to read live weather data and manage a persistent to-do list through MCP tools, demonstrating both read and write capabilities without API keys.

An AI-native Taskwarrior bridge that provides natural language task management for Claude Code and other AI systems, integrating with existing Taskwarrior infrastructure.

Enables AI assistants to interact with Jira and Confluence via natural language, supporting 37 Jira tools and 16 Confluence tools.

Enables search and management of Azure DevOps work items and wiki pages via MCP, wrapping the ado-search CLI.

Enables agents and teams to manage versioned delivery work items, role-tagged handoffs, revision- and source-bound evidence, QA gate evaluation, and release-owner attestations through MCP tools.

Enables deterministic GitHub issue and pull request delivery workflows, including issue creation, development, verification, PR publication, review, and merge, with strict configuration and admission controls.