MCP server that enables communication and coordination between different Roo modes/roles across multiple systems
What is mkc909 agent communication mcp server
Cross-System Agent Communication MCP Server
Overview
This MCP server enables communication and coordination between different Roo modes/roles across multiple systems. It creates a "team of agents" architecture where specialized LLM agents can collaborate on tasks, share context, and coordinate work.
Features
- Agent Registry: Register and manage different Roo modes/roles with their capabilities
- Message Bus: Enable asynchronous communication between agents
- Task Coordination: Manage task assignment and progress tracking
- Context Sharing: Facilitate knowledge transfer between agents
- GitHub Integration: Create and track GitHub issues, manage pull requests
- PlanetScale Integration: Store agent data, messages, and tasks in a scalable database
Architecture
The Cross-System Agent Communication MCP Server consists of three main components:
-
Core MCP Server
- Agent Registry
- Message Bus
- Task Coordination
- Context Sharing
-
GitHub Integration Layer
- Issue Management
- PR Workflow
- Project Management
-
PlanetScale Database Layer
- Agent Data Storage
- Message Storage
- Task Database
Getting Started
Prerequisites
- Node.js 18 or higher
- TypeScript 5.3 or higher
- GitHub API access
- PlanetScale database account
Installation
-
Clone the repository:
git clone https://github.com/mkc909/agent-communication-mcp-server.git cd agent-communication-mcp-server
-
Install dependencies:
npm install
-
Create a
.env
file with the following variables:GITHUB_TOKEN=your_github_token PLANETSCALE_HOST=your_planetscale_host PLANETSCALE_USERNAME=your_planetscale_username PLANETSCALE_PASSWORD=your_planetscale_password
-
Build the project:
npm run build
-
Start the server:
npm start
Development
Running in Development Mode
npm run dev
Running Tests
npm test
Linting
npm run lint
API Endpoints
Agent Management
register_agent
: Register a new agentupdate_agent
: Update agent informationget_agent
: Get agent informationlist_agents
: List all registered agents
Messaging
send_message
: Send message to another agentget_messages
: Get messages for an agentmark_message_read
: Mark message as readdelete_message
: Delete a message
Task Management
create_task
: Create a new taskassign_task
: Assign task to an agentupdate_task_status
: Update task statusget_task
: Get task detailslist_tasks
: List tasks
Context Sharing
create_context
: Create shared contextupdate_context
: Update shared contextshare_context
: Share context with agentget_context
: Get shared contextlist_contexts
: List shared contexts
GitHub Integration
github_create_issue
: Create GitHub issuegithub_comment_issue
: Comment on GitHub issuegithub_create_pr
: Create GitHub PRgithub_review_pr
: Review GitHub PR
License
MIT
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Frequently Asked Questions
What is MCP?
MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications, providing a standardized way to connect AI models to different data sources and tools.
What are MCP Servers?
MCP Servers are lightweight programs that expose specific capabilities through the standardized Model Context Protocol. They act as bridges between LLMs like Claude and various data sources or services, allowing secure access to files, databases, APIs, and other resources.
How do MCP Servers work?
MCP Servers follow a client-server architecture where a host application (like Claude Desktop) connects to multiple servers. Each server provides specific functionality through standardized endpoints and protocols, enabling Claude to access data and perform actions through the standardized protocol.
Are MCP Servers secure?
Yes, MCP Servers are designed with security in mind. They run locally with explicit configuration and permissions, require user approval for actions, and include built-in security features to prevent unauthorized access and ensure data privacy.
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