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.

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.

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.

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.

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.

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 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.

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.

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.

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.

An MCP server based on Anthropic research, providing the 'think' tool capability for Claude AI and enhancing the handling of complex reasoning tasks.

Spec Workflow MCP is a tool that guides AI to systematically complete software development through a structured workflow (requirements → design → tasks) to ensure that code implementation is consistent with business requirements.

An MCP server that connects to the Obsidian knowledge base. Through the REST API plugin, AI agents can perform complex knowledge discovery and analysis tasks, supporting functions such as advanced search, regular expression matching, and full - text retrieval.

A chain of thought MCP server that uses the Groq API to call the Qwen model, enhancing the ability of AI to handle complex tasks through external thinking tools.

A multi - functional MCP server integrating RunwayML and Luma AI APIs, supporting video/image generation and processing tasks

This is an MCP server developed for the Cursor cloud agent API, which allows AI assistants to create and manage cloud agent tasks on GitHub repositories, providing functions such as task creation, status monitoring, and viewing conversation history.

Vibe Check MCP is a server that provides metacognitive supervision for AI agents. Through pattern interruptions, plan simplification, and self - learning feedback loops, it prevents AI from falling into error paths or over - designing solutions in complex tasks.

The AI Cognitive Nexus is a professional AI team collaboration and orchestration system that supports the dynamic creation and management of multi - agent teams to solve complex tasks through hierarchical collaboration.

mcp-micromanage is a tool for controlling and tracking the workflow of AI programming assistants. It ensures that development tasks are executed as planned through mandatory frequent feedback and a visualization dashboard.

The OpenRouter Agents MCP Server is a research agent server based on the Model Context Protocol (MCP). It uses Claude 3.7 Sonnet as the planning agent to coordinate multiple OpenRouter models to decompose and execute complex research tasks, providing efficient and reliable AI research services.

An MCP server based on the CrewAI framework, providing AI agent and task management functions, supporting the creation of agents, tasks, and workflows, and running automatically.

MCP-Odoo is a middleware that connects the Odoo ERP system and AI agents. Through the standardized Model Context Protocol (MCP) interface, AI can access and operate partner information and accounting data (such as invoices and payments) in Odoo, and perform tasks such as financial record reconciliation.

JEBMCP is a project that combines JEB and MCP tools, aiming to simplify reverse engineering tasks through Python scripts and provide efficient code analysis and operation functions.

CrewAI Crew is a multi - agent AI system project based on the crewAI framework, aiming to complete complex tasks through configuration and collaboration.

The MCP Game Helper is a custom model context protocol server that provides AI - assisted tools for game developers, focusing on tasks such as combat balance, skill analysis, level rhythm, and simulation.

Claude Team is a multi - agent MCP server that enables intelligent task distribution, preset workflow templates, and a custom expert system by configuring multiple AI models (such as GPT, Claude, Gemini) to work together, for automated collaboration on complex development tasks.

The OmniFocus MCP Server is a bridge that connects an AI assistant with the OmniFocus task management system, enabling viewing, creation, editing, and deletion of tasks through natural language interaction.

Adaptive Graph of Thoughts is an intelligent scientific reasoning framework based on the Neo4j graph database, which realizes complex scientific reasoning tasks through graph structure and supports integration with AI applications such as Claude Desktop.

Overview: The MCP server acts as middleware, enabling AI agents to automate tasks by connecting to local data and remote services. It supports functions such as query execution and prompting to efficiently handle context. This represents a step towards fully automated AI systems capable of performing complex operations.

MCP Cron is a task scheduling server based on the MCP protocol. It supports scheduling Shell commands and AI tasks through cron expressions and provides task management and execution functions.

The Screeny MCP Server is a privacy-first screenshot service designed specifically for macOS, allowing AI agents to securely capture screenshots of pre-approved application windows and providing a visual context for development and debugging tasks.

Aidderall is an MCP server implementation that provides hierarchical task management functions for AI assistants, helping them maintain focus and context in the process of solving complex problems. By creating independent tasks and subtasks, AI can freely switch focus, complete tasks in any order, and retain all tasks as work records.

MindBridge is an AI model routing server that supports multiple LLM providers, enabling intelligent model scheduling and collaboration, suitable for complex reasoning tasks and multi - model workflows.

A service for interacting with Microsoft To Do tasks via an AI assistant

This is an MCP server project that allows users to define AI sub - agents for specific tasks (such as code review, test writing) in Markdown files and execute them in any MCP - compatible tool through the Cursor, Claude Code, or Gemini CLI backends, realizing the reuse of AI sub - agent workflows across IDEs.

The Sauce Labs MCP Server is a model context protocol server fully integrated with the Sauce Labs testing platform, supporting AI assistants to manage the device cloud, test tasks, build analysis, and monitor the test infrastructure through natural language interaction.

Umbraco MCP is a server based on the Model Context Protocol (MCP), which provides AI - driven background content management functions for Umbraco CMS. It implements secure and permission - controlled automated operations through the Umbraco management API, enabling the AI assistant to perform complex background tasks through natural conversations without manual operation of the interface.

The MCP service tool collection provides API call functions for AI services on Hugging Face and Dify, supporting various NLP, CV, and speech processing tasks.

Swiss MCP is an AI-driven multi-step task coordination center that can integrate various AI tools to complete complex tasks, such as content creation and full-stack application development.

A repository focused on exploring and applying generative AI (GenAI), aiming to help users learn and experiment with the application of GenAI in daily tasks, including writing, programming, image generation, etc., through practical cases and resource sharing.