home / mcp / mcp server deployment mcp server
mcp-server-deployment
Configuration
View docs{
"mcpServers": {
"adarshchaudhary03-mcp-server-deployment": {
"command": "uvx",
"args": [
"--directory",
"/Users/adarshchaudhary/Desktop/ai-projects/mcp-servers/mcp-server-deployment",
"--from",
"git+https://github.com/AdarshChaudhary03/mcp-server-deployment",
"mcp-server"
]
}
}
}The Model-Context-Protocol (MCP) lets a local AI model or agent securely access and act on your development environment by invoking tools exposed by a server. This enables you to perform tasks, retrieve data, and automate workflows right from an AI-enabled client while keeping execution contained within trusted tools you control.
You run a local MCP server and connect an MCP client to it. The server exposes tools the client can call, such as a function to add two numbers. You can build workflows by chaining tool calls and using the local context available to the client.
A tool that takes two integers and returns their sum. This demonstrates a simple function exposed by the MCP server, illustrating how a client can invoke a local operation and receive a computed result.