Local GPU LLM Quantization & Model Context Protocol (MCP) Legal Server

# 1. Shell Script: Launch vLLM Local Inference Engine
python3 -m vllm.entrypoints.openai.api_server \
  --model Qwen/Qwen2.5-70B-Instruct-AWQ \
  --quantization awq \
  --tensor-parallel-size 2 \
  --max-model-len 32768 \
  --gpu-memory-utilization 0.92 \
  --host 127.0.0.1 \
  --port 8000

// 2. TypeScript: Model Context Protocol (MCP) Legal Tools Server
import { Server } from "@modelcontextprotocol/sdk/server/index.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { CallToolRequestSchema, ListToolsRequestSchema } from "@modelcontextprotocol/sdk/types.js";

const server = new Server({
  name: "air-gapped-legal-mcp",
  version: "1.0.0"
}, {
  capabilities: { tools: {} }
});

// Register Statutory Search Tool
server.setRequestHandler(ListToolsRequestSchema, async () => {
  return {
    tools: [
      {
        name: "search_statutory_code",
        description: "Search Indian Penal Code (BNS), Companies Act, and DPDP rules locally.",
        inputSchema: {
          type: "object",
          properties: {
            query: { type: "string" },
            act_name: { type: "string" }
          },
          required: ["query"]
        }
      }
    ]
  };
});

const transport = new StdioServerTransport();
await server.connect(transport);