模型上下文协议

graph TD
    A[AI System] --> B[MCP Protocol]
    B --> C[Reading Files]
    B --> D[Executing Functions]
    B --> E[Handling Contextual Prompts]
    B --> F[Multi-step Tasks]

flowchart LR
    A[Traditional LLM<br/>Knowledge Retrieval] --> B[MCP-Enabled Agent<br/>Task Execution]
    B --> C[Agent Economy]

graph TB
    subgraph "MCP Host (AI Application)"
        H[Host Application<br/>e.g., Cursor, Claude Desktop]
        C1[MCP Client 1]
        C2[MCP Client 2]
        C3[MCP Client N]
    end
    
    subgraph "External Services"
        S1[MCP Server 1<br/>e.g., Filesystem]
        S2[MCP Server 2<br/>e.g., Stripe API]
        S3[MCP Server N<br/>e.g., Database]
    end
    
    H --> C1
    H --> C2  
    H --> C3
    C1 -.->|1:1 Connection| S1
    C2 -.->|1:1 Connection| S2
    C3 -.->|1:1 Connection| S3

sequenceDiagram
    participant User
    participant Host as Host (LLM)
    participant Client as MCP Client
    participant Server as MCP Server

    User->>Host: "What's the status of my latest order?"
    
    Note over Host,Server: Initialization Phase
    Host->>Client: Initialize Connection
    Client->>Server: 1. initialize(capabilities)
    Server-->>Client: 2. initializeResult(capabilities)
    Client->>Server: 3. notifications/initialized
    
    Note over Host,Server: Discovery Phase
    Client->>Server: 4. tools/list
    Server-->>Client: 5. Available tools
    Client->>Host: Provide tools to LLM context
    
    Note over Host,Server: Execution Phase
    Host->>Host: 6. LLM decides on tool
    Host->>Client: 7. Execute tool request
    Client->>Server: 8. tools/call(get_latest_order)
    Server-->>Client: 9. Tool result
    Client->>Host: 10. Return result
    
    Host->>Host: 11. Synthesize response
    Host-->>User: "Your latest order has been shipped."

import { McpServer, StdioServerTransport } from '@modelcontextprotocol/sdk';
import { z } from 'zod';

// 1. Create server instance
const server = new McpServer({
  name: 'weather-server',
  version: '1.0.0',
});

// 2. Define a tool
server.tool(
  'get_weather',
  'Gets current weather for a city',
  z.object({
    city: z.string().describe('City name'),
  }),
  async (params) => {
    const weather = `Weather in ${params.city}: Sunny, 72°F`;
    return {
      content: [{ type: 'text', text: weather }],
    };
  }
);

// 3. Start server
async function main() {
  const transport = new StdioServerTransport();
  await server.connect(transport);
  console.error('Weather MCP server started.');
}

main();

{
  "mcpServers": {
    "local-weather": {
      "command": "node",
      "args": ["/path/to/weather-server.js"]
    },
    "stripe-api": {
      "url": "https://mcp.stripe.com",
      "auth": {
        "type": "bearer",
        "token": "your-api-key"
      }
    }
  }
}

npx @modelcontextprotocol/inspector node server.js

mindmap
  root((MCP Ecosystem))
    AI Providers
      Anthropic
      OpenAI
      Google DeepMind
    Cloud Platforms
      Microsoft Azure
      Google Cloud
      Cloudflare
    Developer Tools
      Cursor
      VS Code
      Sourcegraph
      Replit
    SaaS Platforms
      Stripe
      Figma
      Slack
      Google Drive

graph TB
    A[Security Best Practices] --> B[Server Developers]
    A --> C[Client Developers]
    A --> D[Enterprise Adopters]
    
    B --> B1[Validate Inputs]
    B --> B2[Narrow Permissions]
    B --> B3[Sanitize Outputs]
    
    C --> C1[User Confirmation]
    C --> C2[Sandboxing]
    C --> C3[Access Controls]
    
    D --> D1[VPC Deployment]
    D --> D2[Central Orchestration]
    D --> D3[Audit Trails]

graph LR
    A[HTTP Protocol] --> B[Web Applications]
    C[MCP Protocol] --> D[AI Agent Applications]
    
    style A fill:#e1f5fe
    style C fill:#e8f5e8