ARC Model Context Protocol (MCP) Server
by maxmurphySF
The ARC Model Context Protocol (MCP) Server bridges AI models with the ARC enterprise application framework. It enables AI assistants to leverage ARC's capabilities, accelerating development cycles and enhancing productivity.
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What is ARC Model Context Protocol (MCP) Server?
The ARC Model Context Protocol (MCP) Server is an innovative implementation that follows the Model Context Protocol specification, creating a seamless bridge between AI models (like Claude, GPT, and others) and ARC's robust ecosystem for building cloud-native enterprise applications.
How to use ARC Model Context Protocol (MCP) Server?
To use the ARC MCP Server, clone the repository, install dependencies, build the project, and start the server. Then, configure your AI assistant (e.g., Claude Desktop) to connect to the server by adding the server configuration to the assistant's configuration file.
Key features of ARC Model Context Protocol (MCP) Server
Documentation Assistant (arc.docs.search)
API Microservices Integration (arc.api.authentication, arc.api.notification, etc.)
Project Generation & Scaffolding (arc.generator.microservice)
Deployment Assistance (arc.deployment.infrastructure)
Use cases of ARC Model Context Protocol (MCP) Server
Accelerated Onboarding for new developers
AI-powered code generation for microservices
Streamlined deployment to AWS, Azure, GCP
Contextual search of ARC documentation
FAQ from ARC Model Context Protocol (MCP) Server
What AI models are supported?
What AI models are supported?
The server is designed to work with various AI models like Claude and GPT, as long as they support the Model Context Protocol.
How do I contribute to the project?
How do I contribute to the project?
You can contribute by submitting issues, pull requests, contributing to the documentation, and participating in community discussions.
Where can I find more documentation?
Where can I find more documentation?
Refer to the project's GitHub repository for detailed documentation and examples.
What are the benefits for internal teams?
What are the benefits for internal teams?
Accelerated onboarding, knowledge democratization, standardization, and time savings.
What are the benefits for client projects?
What are the benefits for client projects?
Cost efficiency, consistency, reduced errors, and scalability.