MCP Tooling

The Model Context Protocol (MCP) is an open standard for connecting AI assistants to external tools and data sources. The PAIML stack provides first-class MCP support through two complementary crates:

Why MCP?

MCP enables AI assistants (like Claude) to:

• Execute tools and functions
• Access external data sources
• Integrate with APIs and services
• Maintain stateful sessions

┌─────────────────┐     MCP Protocol     ┌─────────────────┐
│   AI Assistant  │ ◄─────────────────► │   MCP Server    │
│   (Claude)      │                      │   (Your Tools)  │
└─────────────────┘                      └─────────────────┘

Stack Integration

MCP tooling integrates with the broader PAIML ecosystem:

┌─────────────────────────────────────────────────────────┐
│                    MCP Server (pforge)                  │
├─────────────────────────────────────────────────────────┤
│  Tool: train_model    │  Tool: query_data               │
│  → Entrenar           │  → Trueno-DB                    │
├───────────────────────┼─────────────────────────────────┤
│  Tool: run_inference  │  Tool: visualize                │
│  → Realizar           │  → Trueno-Viz                   │
└─────────────────────────────────────────────────────────┘

Quick Start

Option 1: pforge (Recommended)

For most use cases, pforge provides the fastest path to a working MCP server:

# Install pforge CLI
cargo install pforge-cli

# Create new server
pforge new my-ml-server
cd my-ml-server

# Run server
pforge serve

Option 2: pmcp (Low-Level)

For custom implementations or advanced use cases:

use pmcp::{Server, Tool, ToolHandler};

#[tokio::main]
async fn main() {
    let server = Server::new("my-server")
        .with_tool(MyTool::new())
        .build();

    server.serve_stdio().await.unwrap();
}

Use Cases

Next Steps

• pmcp: Rust MCP SDK - Deep dive into the SDK
• pforge: Declarative Framework - YAML-based server development