Agent Orchestration
A

Agent Orchestration

An AI agent collaboration server based on the MCP protocol that solves the coordination problems in multi - agent development, providing functions such as shared memory, task queues, resource locks, and agent discovery, and supporting seamless collaboration across IDEs and CLI tools.
2.5 points
3.4K

What is the Agent Orchestration MCP Server?

Agent Orchestration is an MCP server specifically designed to solve the problems encountered when multiple AI agents (such as Copilot, Cursor, Aider, etc.) collaborate on the same project. It acts like an intelligent 'project manager', enabling different AI assistants to share information, coordinate work, and avoid conflicts, thereby improving overall development efficiency.

How to use Agent Orchestration?

It's very simple to use: 1) Run the initialization command in the project to create a configuration file; 2) Configure your IDE or tool to connect to this MCP server; 3) Start the AI agents, and they will automatically coordinate through this server. The whole process doesn't require complex installation and can be quickly started via npx.

Use Cases

It is most suitable for the development of complex projects that require the collaboration of multiple AI assistants, especially in the following scenarios: when the team uses different AI tools, when large - scale projects require division of labor and collaboration, when avoiding work conflicts between AI assistants, and when projects need to maintain consistency in the development context.

Main Features

Shared Memory System
All AI agents can store and read shared information, including project context, technical decisions, discovered problems, etc., ensuring that all assistants have a consistent understanding of the project status.
Task Coordination Queue
An intelligent task queuing and execution system that ensures AI assistants work in order, avoiding multiple assistants modifying the same file or performing the same task simultaneously.
Agent Discovery and Registration
Automatically discover all AI assistants working in the project, allowing each assistant to know who else is involved in the project, facilitating division of labor and collaboration.
Resource Locking Mechanism
Prevent multiple AI assistants from editing the same file simultaneously, avoiding code conflicts and overwrites, and ensuring the security of modifications.
Automatic Context Synchronization
Automatically update the activeContext.md file of the project, providing the latest project status and decision records for all AI assistants.
Wide Compatibility
Supports all mainstream AI coding assistants, including Cursor, Copilot, Aider, Windsurf, etc., as well as any tools that follow the AGENTS.md standard.
Advantages
Eliminate conflicts between AI assistants: Avoid multiple assistants modifying the same file simultaneously through a coordination mechanism.
Improve collaboration efficiency: Agents can divide labor and cooperate, each handling tasks they are good at.
Maintain context consistency: All assistants share the same project status and understanding.
Reduce duplicate work: Avoid multiple assistants performing the same task.
Easy to integrate: No complex configuration is required, and you can start using it within minutes.
Open - source and free: Based on the MIT license, it can be used completely for free.
Limitations
Requires AI assistants to support the MCP protocol: Some older AI tools may not support it.
Learning curve: You need to understand basic coordination concepts and work processes.
Dependent on the project environment: It needs to be configured separately in each project.
Currently only supports local coordination: It does not support cross - team or remote collaboration for now.

How to Use

Initialize the Project
Run the initialization command in the project root directory to create the necessary configuration files.
Configure the IDE or Tool
Configure the MCP server connection according to the AI tool you are using. Take Cursor as an example, edit the configuration file.
Start the MCP Server
The server will start automatically, and you can also manually run the service command.
Start Using AI Assistants
Start your AI coding assistants, and they will automatically coordinate through the MCP server.
Monitor the Coordination Status
Use the provided tools to view the status, task queue, and shared information of all current AI assistants.

Usage Examples

Multi - Agent Collaborative Development of New Features
The main AI assistant is responsible for the architecture design, creates multiple sub - tasks, and then multiple sub - AI assistants claim different parts (such as front - end components, back - end APIs, database migrations) and develop in parallel.
Code Review and Refactoring
One AI assistant is responsible for code review. After finding problems, it creates refactoring tasks, and another AI assistant claims and performs the refactoring while ensuring that the existing functions are not damaged.
Team Using Different AI Tools
Team members use different tools such as Cursor, Copilot, Aider, etc. Through the MCP server, they share the project context and decisions, ensuring that everyone has a consistent understanding of the project.

Frequently Asked Questions

What do I need to install to use this service?
Will this service affect my existing use of AI assistants?
What will happen if the MCP server stops running?
Is this service secure? Will it leak my code?
Which AI coding assistants are supported?
How can I view which AI assistants are currently working?

Related Resources

GitHub Repository
The project's source code, issue tracking, and contribution guidelines.
AGENTS.md Standard
An open standard for AI coding assistants, used by more than 60,000 open - source projects.
Model Context Protocol
The official documentation and specifications of the MCP protocol.
npm Package Page
View the latest version and download statistics.

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "agent-orchestration": {
      "command": "npx",
      "args": ["-y", "agent-orchestration", "serve"],
      "env": {
        "MCP_ORCH_SYNC_CONTEXT": "true"
      }
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

Alternatives

A
Airweave
Airweave is an open - source context retrieval layer for AI agents and RAG systems. It connects and synchronizes data from various applications, tools, and databases, and provides relevant, real - time, multi - source contextual information to AI agents through a unified search interface.
Python
7.9K
5 points
V
Vestige
Vestige is an AI memory engine based on cognitive science. By implementing 29 neuroscience modules such as prediction error gating, FSRS - 6 spaced repetition, and memory dreaming, it provides long - term memory capabilities for AI. It includes a 3D visualization dashboard and 21 MCP tools, runs completely locally, and does not require the cloud.
Rust
5.4K
4.5 points
M
Moltbrain
MoltBrain is a long-term memory layer plugin designed for OpenClaw, MoltBook, and Claude Code, capable of automatically learning and recalling project context, providing intelligent search, observation recording, analysis statistics, and persistent storage functions.
TypeScript
5.3K
4.5 points
B
Bm.md
A feature-rich Markdown typesetting tool that supports multiple style themes and platform adaptation, providing real-time editing preview, image export, and API integration capabilities
TypeScript
4.5K
5 points
S
Security Detections MCP
Security Detections MCP is a server based on the Model Context Protocol that allows LLMs to query a unified security detection rule database covering Sigma, Splunk ESCU, Elastic, and KQL formats. The latest version 3.0 is upgraded to an autonomous detection engineering platform that can automatically extract TTPs from threat intelligence, analyze coverage gaps, generate SIEM-native format detection rules, run tests, and verify. The project includes over 71 tools, 11 pre-built workflow prompts, and a knowledge graph system, supporting multiple SIEM platforms.
TypeScript
5.6K
4 points
P
Paperbanana
Python
7.9K
5 points
B
Better Icons
An MCP server and CLI tool that provides search and retrieval of over 200,000 icons, supports more than 150 icon libraries, and helps AI assistants and developers quickly obtain and use icons.
TypeScript
6.7K
4.5 points
A
Assistant Ui
assistant - ui is an open - source TypeScript/React library for quickly building production - grade AI chat interfaces, providing composable UI components, streaming responses, accessibility, etc., and supporting multiple AI backends and models.
TypeScript
6.7K
5 points
N
Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
20.7K
4.5 points
G
Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
25.1K
4.3 points
M
Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
36.1K
5 points
D
Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
73.9K
4.3 points
F
Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
65.8K
4.5 points
U
Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
32.1K
5 points
G
Gmail MCP Server
A Gmail automatic authentication MCP server designed for Claude Desktop, supporting Gmail management through natural language interaction, including complete functions such as sending emails, label management, and batch operations.
TypeScript
22.3K
4.5 points
M
Minimax MCP Server
The MiniMax Model Context Protocol (MCP) is an official server that supports interaction with powerful text-to-speech, video/image generation APIs, and is suitable for various client tools such as Claude Desktop and Cursor.
Python
50.3K
4.8 points
AIBase
Zhiqi Future, Your AI Solution Think Tank
© 2026AIBase