"AI-Based Task Management System" matching MCP servers:

Enables Claude to interact with System Task projects, teams, and tasks, providing daily briefs, project reports, team load, and risk identification, as well as creating and updating tasks and demands.

Enables comprehensive task management with groups, custom statuses, and task relationships, designed for AI assistants to manage tasks during conversations.

About Your task manager is the best agent memory you're not using. An agent-native context layer over your existing task app.

A task management system for LLM-based agents that stores all tasks in a single tree, available immediately after the server starts.

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.

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.

HR Management AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Project Management AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Enables AI agents to create, manage, and track tasks within plans using Valkey as the persistence layer. Supports plan and task management with Markdown notes, status tracking, and prioritization through multiple transport protocols (SSE, Streamable HTTP, STDIO).

A sophisticated task orchestration system with role-based workflow management and Trello integration.

Inventory Management AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Enables intelligent task management with status tracking, dependency resolution, and automatic next task discovery based on preconditions and priorities. Supports hierarchical task structures with subtasks and flexible JSON-based configuration.

A task management system that exposes CRUD operations for todos through a custom MCP protocol, enabling AI agents and CLI tools to create, read, update, and delete tasks using JSON-based communication over stdin/stdout.

A Node.js-based AI agent system using Model Context Protocol (MCP) that provides financial analysis and portfolio management services through LangChain and Ollama-powered local AI models.

A cross-AI-agent local task context sharing MCP server that allows clients like Codex, Claude Code, Hermes, and VS Code to read and write the same task state, enabling task tracking and context distillation.

Lets AI assistants classify an AI system under the EU AI Act, returning risk tier, obligations, and deadlines based on a plain-English description of the product.

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.

Provides task and project management tools for AI agents, including todo list management, prioritization frameworks like Eisenhower Matrix and RICE scoring, time estimation using PERT, daily standup generation, and sprint burndown calculation.

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

MCP server for Cognigy.AI - 132 tools that let Claude, Cursor & other AI assistants build, configure, test & operate conversational AI agents via the Model Context Protocol.