# Workflow

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.

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

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 Kanban is a task management toolset designed for AI agents. It manages multi-session workflows through a kanban system, supports column capacity limits, an embedded database, and Web UI monitoring. It provides API interfaces for creating, moving, and deleting tasks, as well as preset prompt words to assist in project initiation and advancement.

This is an MCP server that provides integration for Linear issue tracking and project management, supporting functions such as creating and searching for issues, managing sprints, and teams.

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.

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.

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.

This project is an interactive feedback MCP server, aiming to optimize the workflow of AI assistants, reduce unnecessary tool calls by requesting user feedback, improve efficiency, and save resources.

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.

A Jira connection tool based on the Go language, supporting AI assistants to interact with Jira through the MCP protocol to achieve functions such as issue management and workflow operations.

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.

Agentis MCP is a flexible multi - agent framework for building powerful AI agents, supporting MCP server connection, and providing functions such as tool access, resource retrieval, and multi - agent workflow orchestration.

MCP service integration for the Productboard API

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.

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

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.

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.

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.

00_master_mcp is the core coordinator of the MCP multi - agent system, responsible for managing the connections of all downstream service containers, context routing, security policy enforcement, and complex workflow orchestration, and providing a unified SSE endpoint for external tools to access.

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.

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.

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

This project manages the configuration rules of AI agents through the Cursor IDE, including rule editing and synchronization mechanisms, and is mainly applied to the workflows of professional agents and development agents.

An implementation of the Unstructured API MCP server, providing tools for interacting with the Unstructured API, including operations such as creating, updating, and deleting data sources, workflows, and tasks.

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.

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 contains AI - assisted workflow templates for Angular component refactoring and design system migration, providing a structured and step - by - step guidance for complex refactoring operations.

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.