PraisonAI is a production-ready multi-AI agent framework with self-reflection capabilities, designed to create AI agents to automate the solution of various problems from simple tasks to complex challenges. It simplifies the construction and management of multi-agent LLM systems by integrating PraisonAI agents, AG2, and CrewAI into a low-code solution, emphasizing simplicity, customization, and effective human-machine collaboration.

wcgw is an MCP server project that integrates Shell and code editing tools, allowing AI to execute commands, read and write files, edit code, etc. on the local machine. It provides multiple modes (such as Architect Mode, Code Writing Mode, etc.), supports task checkpoint saving, terminal interaction, syntax checking, etc., and is suitable for scenarios such as code development and problem troubleshooting.

Zen MCP is a multi-model AI collaborative development server that provides enhanced workflow tools and cross-model context management for AI coding assistants such as Claude and Gemini CLI. It supports seamless collaboration of multiple AI models to complete development tasks such as code review, debugging, and refactoring, and can maintain the continuation of conversation context between different workflows.

Open Multi - Agent Canvas is an open - source multi - agent chat interface that supports managing multiple agents in dynamic conversations for travel planning, research, and general task processing.

The Apify MCP Server is a service that implements the Model Context Protocol (MCP), allowing AI assistants to interact with various Actors on the Apify platform through SSE or Stdio to perform tasks such as data scraping and web search.

A software development planning tool based on the MCP protocol, providing functions such as task decomposition, progress tracking, and development plan management

An MCP server integrating Claude and Todoist, supporting natural language task management

A software development planning tool based on the Model Context Protocol (MCP), which provides functions for task breakdown, progress tracking, and development plan management to help teams efficiently plan software development projects.

The Neon MCP Server is an open - source tool that allows users to interact with the Neon Postgres database through natural language, simplifying database management tasks.

ATLAS is an intelligent task and knowledge management system built on TypeScript and Neo4j, designed for LLM agents, providing a three - layer management architecture for projects, tasks, and knowledge.

The ClickUp MCP Server is a model context protocol server for integrating ClickUp tasks with AI applications, supporting task, space, list, and folder management through a standardized protocol.

An intelligent task management system based on the MCP protocol, providing an efficient programming workflow framework for AI agents, with functions such as task planning, decomposition, execution, and memory.

IDA Pro MCP Server is a plugin that enables remote interaction between AI assistants and IDA Pro through the Model Context Protocol interface, supporting binary analysis tasks such as disassembly, pseudocode retrieval, and function query.

MCPBench is a framework for evaluating the performance of MCP servers. It supports the evaluation of two types of tasks: web search and database query, is compatible with local and remote servers, and mainly evaluates accuracy, latency, and token consumption.

The Aider MCP Server is an experimental model context protocol server used to offload AI coding tasks to Aider, improving development efficiency and flexibility.

The Kubernetes MCP Server is a powerful implementation of the Kubernetes model context protocol, supporting operations on Kubernetes and OpenShift clusters. It can perform various resource management tasks without relying on external tools.

The ClickUp MCP Server is a model context protocol server for integrating ClickUp tasks with AI applications. It supports managing tasks, spaces, lists, folders, etc. through a standardized protocol and provides functions such as time tracking and tag management.

This is a Label Studio integration server based on the Model Context Protocol, which realizes programmatic interaction with Label Studio instances through the label - studio - sdk, supporting functions such as project management, task management, and prediction integration.

The Meta Prompt MCP project simulates a multi - agent collaboration system through a single language model, realizing task decomposition and expert consultation functions, and simplifying the process of solving complex problems.

An efficient task manager that supports multiple file formats (Markdown, JSON, YAML), provides powerful search, filtering, and organization functions, and is designed to minimize tool confusion and maximize LLM budget efficiency.

SAGE - MCP is an intelligent AI assistant MCP server that offers multiple working mode selections, conversation continuity management, and intelligent file handling functions. It can automatically select the best AI model based on task complexity.

A server based on the Model Context Protocol for managing GitLab kanban task operations, providing functions such as task list query, creation, update, deletion, and commenting.

An MCP server based on containerized Kali Linux that provides the ability to execute commands for penetration testing and security research tools, supporting background task management and interactive vulnerability detection.

An MCP server implemented based on go - mcp, used for automated vulnerability scanning tasks in emergency response. It supports generating POCs, creating scanning tasks and workflows, and is compatible with both HTTP API and MCP protocol.

The TickTick MCP Server is a task management API service, providing complete task and project management functions, including task creation/updating, project organization, habit tracking, etc., supporting OAuth authentication and rich custom options.

The Project MCP Server is a tool for managing project knowledge graphs, providing structured representations of projects, tasks, milestones, resources, and team members to help project managers track progress, manage risks, allocate resources, and make decisions.

LLMling is a Python library that provides a configurable LLM task processing framework, supporting multiple context processors and LLM provider integrations.

An MCP server based on TypeScript that integrates the text-to-image and text-to-video APIs of Tongyi Wanxiang, supporting asynchronous task processing and the MCP protocol specification.

A project that exposes AutoHotkey functionality through an MCP server, enabling model interfaces to control Windows automation tasks.

Think MCP is a project that implements an MCP server, providing the 'think' tool to support AI agents in performing structured reasoning in complex tasks, inspired by Anthropic's research. This tool helps AI process information, backtrack, or adhere to strategies by recording the thinking process, and is suitable for scenarios such as tool output analysis, policy-intensive environments, and sequential decision-making.

A local task management server based on SQLite, following the MCP protocol, providing project-based task management tools that support operations such as creating projects, adding tasks, updating statuses, and expanding subtasks.

Speelka Agent is a general LLM agent based on the Model Context Protocol (MCP), capable of invoking tools from other MCP servers to achieve complex task decomposition, multi - model collaboration, and tool orchestration.

Teamwork MCP is a server that connects to the Teamwork API, providing a simplified interface to manage projects and tasks.

A terminal-based MCP protocol scheduled task management tool that provides a visual interface to view and monitor crontab tasks

Bonsai - mcp is a Blender plugin that implements the analysis and operation of IFC building models through IfcOpenShell, supporting the execution of building information model query tasks through interaction with LLMs such as Claude.

The Kanboard MCP Server is a model context protocol server developed in Go that enables seamless integration between AI assistants and the Kanboard project management system. It supports managing projects, tasks, users, and workflows through natural language commands.

DINO-X MCP is a project that enables large language models to perform fine-grained object detection and image understanding through DINO-X and Grounding DINO 1.6 API. It can achieve precise object positioning, counting, attribute analysis, and scene understanding, and supports natural language-driven visual tasks and workflow integration.

Yokan Board MCP is a server based on Model Context Protocol that provides a tool interface for AI agents to interact with Yokan Kanban API, supporting comprehensive management of Kanban, columns, and tasks.

The TickTick MCP Server is a service that implements the Model Context Protocol (MCP), allowing AI assistants to interact with the TickTick task management application through the TickTick Open API and providing task and project management functions.

An MCP server based on Cloudflare Workers, used to send notifications to Discord when tasks are completed by Claude Code, supporting rich text formats and multiple transport protocols.