"Understanding the term 'throw' in web contexts" matching MCP servers:

Enables MCP-compatible assistants to connect to a user's workspace, read across boards, notes, checklists, habits, money, meals, chores, and chat, and make scoped additions, changes, or removals with attribution.

Enables AI assistants to create and manage visual automation configurations, workflows, and UI states through the Qontinui API. It supports project management, workflow execution, and configuration handling for automated web interactions.

Enables people to open a shared group chat as a card inside their own AI chat, where they and their AIs talk together and post, claim, and confirm tasks on a self-organizing board. Its tools also let any AI read the repository's code and submit a proposed change that becomes a pull request.

Goodday‑MCP is a lightweight Model Context Protocol (MCP) server designed to seamlessly integrate with the Goodday project management platform via its API v2. It enables querying of projects, tasks, and users—without altering any data—making it ideal for secure context-aware applications

Enables comprehensive management of OpenProject work packages, projects, comments, and relations through natural language. Supports creating, updating, and organizing tasks with assignees, watchers, hierarchies, and inter-task relationships.

An MCP server for managing Tempo worklogs in Jira, allowing users to track time, retrieve logs, and perform bulk operations via natural language. It integrates with the Tempo API to support creating, editing, and deleting work entries through MCP-compatible clients like Claude and Cursor.

Enables proof-carrying project execution through a read-only remote MCP endpoint and WebMCP tools for managing Project Passports, task graphs, evidence-backed provider comparisons, route approvals, artifacts, verification records, and checkpoints without executing external providers.

A Model Context Protocol (MCP) server for Hubstaff API integration, enabling seamless time tracking, project management, and team collaboration through AI assistants.

Connects Claude Desktop to Canvas LMS to monitor academic activities like assignments, announcements, and upcoming deadlines. It enables users to track courses and pending tasks through a unified interface using the Canvas REST API.

Exposes a curated set of Bot Army tools (chat, GTD tasks, docs search, dice roll) to external SSE-only MCP clients via authenticated SSE transport.

Enables submitting team check-ins to Steady (app.steady.space) by automating the web form through login, team discovery, and check-in submission with previous/next/blockers fields.

A Model Context Protocol (MCP) server that integrates with Zentao's RESTful API to manage bugs, including listing, resolving, closing, and commenting, with support for product and project set contexts.

MCP server providing access to JIRA data with relationship tracking, optimized payloads, and data cleaning for AI contexts. Supports both Jira Cloud and Server/Data Center.

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.

Simple MCP Server to enable a human-in-the-loop workflow in tools like Cline and Cursor. This is especially useful for developing desktop applications that require complex user interactions to test.

Provider agnostic ai orchestrator layer, kagan mcp allows controlling orchestrating and spawning subagents via mcp associated with tasks in kanban board that is accessible via kagan cli executable that bundles a chat repl, tui , mcp and a web client in a single uv tool install kagan wheel. Give it a try and submit feedback and feature requests! Consider starring the repo, its a free oss MIT based.

Integrates with the addTaskManager iOS/macOS app to manage tasks, projects, and ideas through the ADD (Assess-Decide-Do) framework. Enforces realm-based restrictions where users can create/edit content in Assess, assign contexts/dates in Decide, and mark items complete in Do.

TruePPM MCP servers ask real questions of your self-hosted TruePPM instance: the critical path, a Monte Carlo slip forecast, sprint status, the risk register, My Work. Answers are computed server-side by the same CPM/Monte Carlo engine the web UI uses, never guessed by a model, and nothing leaves your box.

Run your Tallyfy workflows from any AI assistant in plain English. 107 tools across processes, tasks, templates, form fields, automation rules, users, and search, each scoped to the signed-in user's Tallyfy permissions.

Connects AI clients to an enterprise resource scheduling platform so agents can view schedules and availability, track projects, bookings and allocations, manage timesheets, and run utilization, forecast and financial reports using the signed-in user's permissions.