# Workflow Management

NeoCoder is an AI programming assistance system based on the Neo4j knowledge graph. It enables the interaction between AI assistants and the knowledge graph through an MCP server, providing standardized coding workflows, dynamic instruction manuals, and project memory functions. The system supports multiple operation modes (incarnations), including basic programming, scientific research, decision - making analysis, complex system modeling, knowledge graph management, and code analysis. It stores workflow templates and execution records in Neo4j to ensure the traceability and standardization of the coding process.

The TypeScript version of MCP Agent is a TypeScript-based intelligent context-aware agent framework that provides features such as a modular architecture, advanced workflow management, a powerful logging system, and a flexible executor. It is a TypeScript port of the original MCP Agent.

The MCP integration service for Azure DevOps provides a standardized access interface to work items, code repositories, projects, kanban boards, and iterations.

The Procesio MCP Server is a middleware that interacts with the Procesio automation platform API, providing workflow management and instance operation functions.

An MCP protocol server implemented for Apache Airflow, providing a standardized interface to interact with Airflow

The Bio-OS MCP Server is a tool and prompt server based on the model context protocol, providing workflow management and Docker image building functions for Bio-OS, supporting both local and cloud deployment methods.

An n8n workflow management protocol server designed for AI assistants, supporting the creation, execution, and monitoring of workflows through natural language interaction.

An MCP server designed for n8n workflow automation, providing a standardized JSON-RPC interface to execute and manage workflows

DolphinScheduler MCP Server is a server based on FastMCP that exposes DolphinScheduler's REST APIs as a standardized toolset for AI agents, enabling AI - driven process management.

Cloudera AI Agent Studio MCP Server is a lightweight model context protocol bridge service that can expose Agent Studio instances as a set of callable tools, supporting dynamic creation and management of workflows.

MCP Agile Flow is an AI - assisted agile development workflow management system based on FastMCP, providing RESTful APIs and a resource - prioritized architecture, supporting natural language command processing and multi - IDE integration.

This project provides a Dagster service interface based on the Model Context Protocol, enabling AI agents to interact with the Dagster data orchestration platform for data pipeline exploration, run monitoring, and asset management.

Swytchcode MCP server implementation for interacting with Swytchcode, supporting the invocation of Swytchcode API functions through Claude Desktop.

This project provides an MCP server for the JobNimbus API, enabling AI assistants to access and manipulate JobNimbus data, including workflow information such as contacts, tasks, and products, through a standardized tool.

An MCP server designed for Prefect that allows AI assistants to interact with Prefect through natural language and supports multiple functions such as workflow management and deployment management.

The n8n MCP Server is a service that provides access to n8n workflows, executions, credentials, etc. through the Model Context Protocol, enabling large language models to interact with n8n instances in a secure and standardized manner.

BRAINS OS is an AI operating system based on modern cloud-native technologies, designed specifically for managing large language models and dedicated AI agents, providing visual workflow editing, a unified command system, and a secure deployment framework.

A Python-based MCP server for guiding agents to execute tasks according to predefined structured workflows while maintaining execution flexibility.