"A production-ready Task Management MCP server for AI agents and autonomous workflows" matching MCP servers:

Enables AI agents to manage n8n workflow automation instances through tools for workflow CRUD operations, execution monitoring, and webhook triggering. It facilitates programmatic interaction with n8n instances via the n8n API with AI-optimized descriptions and error handling.

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.

Run YAML workflows as MCP tools so agents can automate real tasks with one server.

MCP server for authoring, validating, simulating, and publishing workflows for the Runbook workflow engine, including branch and run management.

An MCP server that turns deployed n8n workflows into callable tools for AI agents, enabling discovery and execution of tagged workflows via a standard interface without rewriting integrations.

Manage Job using MCP: Manage Job, Candidates, Resumes, Salaries all within this one MCP tools It can solve problems like: You have 50 resumes to screen. Your AI assistant can reason about candidates, but it can't: Read PDFs/DOCX — The AI can't open binary files Extract structured data — Copy-pasting loses formatting, metrics, and context Compare at scale — No consistent scoring across candida

Enables an AI assistant to estimate federal Canada Child Benefit amounts, check eligibility, explain rules, and prepare and verify a filled RC66 application for the user to review and sign.

Enables agents to persist and resume long-horizon tasks using cryptographic event-sourced checkpoints, idempotency deduplication, scheduled heartbeats, pause/resume tokens, and fail-safe recovery.

Elevate your LLM task management with Task Orchestrator, an MCP server that empowers you to define, organize, and track goals and tasks with hierarchical precision. Integrate intelligent task management into your workflow.

Gives your AI assistant full control of a Discord server: 148 tools for chat, moderation, automod, events, and administration, up to building a complete community server from one paragraph. Every destructive action previews first and waits for your confirmation.

Enables users to manage tasks through a simple JSON file interface. Provides basic task management functionality by reading and writing to a configurable tasks.json file.

Enables an AI agent to operate a spare Android phone through MCP: capture screenshots, inspect UI controls, tap/swipe, input Chinese text, launch apps, and optionally run rooted shell commands or transfer files. It also supports a live web console for remote viewing and control.

Enables AI assistants to manage Dida365 (滴答清单) tasks through the Model Context Protocol. It supports full task lifecycle management including creating, updating, and filtering tasks with automatic timezone handling.

A remote MCP server that lets AI agents build, run, and manage Automat RPA workflows.

An MCP (Multi-Agent Conversation Protocol) Server that enables interaction with Google Workflows API, allowing management of workflow executions and definitions through natural language commands.

An MCP server for task orchestration.

Enables AI agents to programmatically create, manage, and execute independent Python workflow scripts with full CRUD operations, allowing AI to build and modify automation workflows themselves rather than just executing pre-built ones.

Enables AI assistants to manage tasks through a comprehensive interface with 8 tools for creating, updating, searching, and tracking tasks with priorities, categories, and due dates. Features persistent file-based storage, advanced filtering, and task statistics for complete task management workflow.

Well-designed PDFs from a single prompt. Describe what you need, get a professional document.

A Model Context Protocol implementation that provides a standardized interface for task management, supporting both STDIO mode for CLI/AI applications and HTTP+SSE mode for browser-based clients.