# Workflow

The UNS-MCP Server is an MCP server implementation for interacting with the Unstructured API, providing various tools to manage data sources, workflows, and jobs.

The Apple MCP toolset is a collection of native Apple tools designed for the MCP protocol, supporting multiple functions such as messages, notes, contacts, emails, reminders, and calendars.

This is an AI automated editing tool designed for Adobe Premiere Pro, which realizes natural language control and automated workflow through the MCP protocol.

An MCP server that provides city weather information, realizing weather data query and natural - language processing functions through APIs and tool - based workflows.

This project is a ComfyUI workflow pipeline wrapper designed for Open WebUI. It implements image generation functionality through the comfy - mcp - server and needs to be used in conjunction with ComfyUI and Open WebUI Pipelines.

AI Session Handover Management Service

A server based on the FastMCP framework that generates images according to prompts through a remote Comfy server.

The TimeCamp MCP Server is a hosted service based on Cloudflare Workers, providing API functions integrated with the TimeCamp time management tool, including operations such as creating, querying, updating, and deleting time records.

The ComfyUI MCP Server is a service implementation for integrating ComfyUI with MCP. It needs to be used with a running ComfyUI server and provides multiple built-in tools such as text-to-image generation, image downloading, and running custom workflows. It supports running in UV or Docker mode.

Data Agents is a GenAI - based data engineering agent platform that automates data workflows through multi - agent collaboration, supports multiple AI backends and n8n integration, and provides a modern UI interface and Docker deployment solution.

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.

A collection of MCP server examples provided by AWS GCR, covering various functions such as remote desktop, workflow services, AI planning, time services, and HTML rendering

The Gemini CLI Orchestrator is a multi-step code analysis tool based on Google Gemini AI. It guides developers through a systematic analysis via a structured workflow rather than replacing human thinking. It offers four core functions: analysis planning, prompt optimization, iterative analysis, and result synthesis, and is suitable for complex scenarios such as security audits and performance optimization.

Kanban MCP is a project that connects the Planka kanban board with the Cursor MCP protocol, enabling AI assistants to manage kanban tasks, including creating/moving cards, tracking time, adding comments, etc., to achieve human-machine collaborative workflow management.

The Flashduty MCP Server is a server based on the Model Context Protocol that provides seamless integration with the Flashduty API and supports event management and automation functions.

The Plane MCP Server is a model context protocol server that provides seamless integration with the Plane API, supporting functions such as project management, work item operations, and automation processes. It is suitable for developers and AI tool integration.

This project implements an MCP server that integrates Venice AI's image - generation capabilities, providing an interactive image - generation service with an approval/regeneration workflow and supporting the generation of multi - view 3D views through the Gemini API.

A Golang-based MCP-compatible server for running Argo workflows

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 - agent is a lightweight AI agent framework based on the Model Context Protocol (MCP), which supports building efficient agent applications through a simple and composable model. It integrates the lifecycle management of the MCP server and implements multiple workflow models, such as parallel processing, routing, evaluation optimization, etc., and is suitable for various AI application scenarios such as multi - agent collaboration and human - machine interaction.

An AI-assisted software development workflow tool based on specification-driven development, providing a real-time dashboard to monitor project progress and document management.

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.

Enterprise-level MCP server, integrating ServiceNow and workflow management, providing health monitoring and a high-performance FastAPI backend.

MCP is an open protocol for standardizing the context of AI applications, similar to the USB - C interface in the AI field, enabling seamless connection between LLMs and various data sources/tools. It provides preset integrations, multi - model switching, secure data processing, and a standardized interface, supporting the construction of LLM - based intelligent agents and complex workflows.

The Razorpay MCP Server is an official payment integration service that provides seamless docking with the Razorpay API through the Model Context Protocol (MCP), supporting multiple payment tools and automated processes.

MCP service integration for the Productboard API

An example project of an MCP server demonstrating how to chat with DeepSeek and use MCP tool calls.

This is an AI development tool project based on Docker containers. It uses Markdown files to write complex workflows, combines Dockerized tools with the LLM model selected by the user, and implements a workflow of multi - model agents and project - priority design.

Quick-start Auto MCP is a tool that helps users quickly register the Anthropic Model Context Protocol (MCP) in Claude Desktop and Cursor. It provides functions such as RAG document search, Dify workflow, real-time web search, and supports one-click generation of JSON configuration files.

This project has configured GitHub Actions workflows for testing Plane.so API endpoints, including unit tests and integration tests. You need to configure API keys and the workspace slug as keys.