"Using AI to Generate XUI Content on a Whiteboard" matching MCP servers:

An MCP server that uses AI to generate structured Asana project plans from diverse sources like text, PDFs, and meeting transcripts. It enables users to preview, generate, and directly sync detailed task lists, subtasks, and dependencies into Asana.

One-pass agentic inbox triage as an MCP server: fetch unread Gmail → classify (action_needed/fyi/newsletter/noise) → summarize → extract tasks → draft replies as Gmail DRAFTS (never sends) → flag calendar → write a triage report. Four stdio tools (fetch_emails, save_gmail_draft, append_tasks, write_report); the host is the LLM, so it runs keyless in Claude Code. Gmail scopes: readonly + compose

Enables MCP-capable agents to fetch work from Slack threads, propose GitHub issues or updates, link messages to topics, ask the channel questions, and report write results, with human approval gates for GitHub actions.

Enables agentic co-authoring of feature specs, decomposition into architecture-validated tickets, and idempotent syncing to Linear as projects with epics, sub-issues, and dependencies.

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 AI clients like Claude to read and manage Microsoft To Do task lists and tasks via the Microsoft Graph API, running locally over stdio with secure token storage.

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.

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 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 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.

On Board is a local MCP server that gives multiple AI agents and IDEs a shared project memory, ticket queue, and handoff history, so agents can seamlessly continue each other's work. It supports agent-to-agent wake events, enabling autonomous workflows like reject-fix-resubmit cycles without human relay.

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.

Enables managing Microsoft To Do lists and tasks through MCP, including creating, updating, completing, deleting, searching, and checklist operations via Microsoft Graph.

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.

Enables to manage to-do items through natural language, with tools for creating, reading, updating, and deleting tasks.

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

Enables AI clients to access a shared, authenticated memory and project management system with durable storage, task tracking, roadmaps, and semantic search, deployed on Cloudflare.

Provides a shared task state for local coding agents, letting them bootstrap a project, list and create tasks, resume work, write checkpoints, inspect configured routes, and plan worker runs. It also exposes a bounded delegation call that invokes configured local agent clients, returning a proposal that requires human review since it may consume quota or balance.

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.

Enables management of TestMu AI test projects, test cases, test runs, and integration with Jira, HyperExecute, and AI insights through natural language.