🔗 MCP协议2026：AI Agent的通信革命

# 2026年：无状态HTTP传输
POST /mcp/v1/messages
Content-Type: application/json

{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "name": "get_weather",
    "arguments": {"city": "Shanghai"}
  },
  "id": 1
}

# 响应（无需保持连接）
{
  "jsonrpc": "2.0",
  "result": {"temperature": 28, "unit": "celsius"},
  "id": 1
}

# 创建异步任务
POST /mcp/v1/tasks
{
  "method": "long_running_analysis",
  "params": {"data": "large_dataset.csv"},
  "callback": "https://your-server.com/webhook"
}

# 响应
{
  "task_id": "task_abc123",
  "status": "pending",
  "estimated_time": "5m"
}

# 任务完成时回调
POST https://your-server.com/webhook
{
  "task_id": "task_abc123",
  "status": "completed",
  "result": {"insights": [...]}
}

# 企业级OAuth认证
POST /mcp/v1/auth/token
{
  "grant_type": "client_credentials",
  "client_id": "your_enterprise_id",
  "client_secret": "your_secret",
  "scope": "mcp:tools:read mcp:tools:execute"
}

# 响应
{
  "access_token": "eyJhbGciOiJSUzI1NiIs...",
  "token_type": "Bearer",
  "expires_in": 3600,
  "scope": "mcp:tools:read mcp:tools:execute"
}

# Agent间直接通信
POST /mcp/v1/agents/agent_123/message
{
  "from": "agent_456",
  "type": "collaboration_request",
  "payload": {
    "task": "data_analysis",
    "data_source": "sales_2026.csv",
    "deadline": "2026-06-06T12:00:00Z"
  }
}

# Agent 123 响应
{
  "status": "accepted",
  "estimated_completion": "2026-06-06T10:00:00Z",
  "collaboration_id": "collab_xyz789"
}

┌─────────────┐    ┌─────────────┐    ┌─────────────┐
│   AI Model  │───▶│ MCP Client  │───▶│ MCP Server  │
│  (Claude等) │    │  (客户端)   │    │  (服务器)   │
└─────────────┘    └─────────────┘    └─────────────┘
                           │                   │
                           ▼                   ▼
                    ┌─────────────┐    ┌─────────────┐
                    │   Transport │    │   Tools &   │
                    │   (传输层)  │◀──▶│  Resources  │
                    └─────────────┘    └─────────────┘
                           │
                           ▼
                    ┌─────────────┐
                    │    Auth     │
                    │   (认证)    │
                    └─────────────┘

📊 MCP生态系统统计
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🏢 注册服务器：19,831+
📥 月度SDK下载：97,000,000+
👥 支持企业：Anthropic, OpenAI, Google, Microsoft
📦 社区贡献：5,200+ 开发者
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

# OpenClaw MCP配置
# ~/.openclaw/config.json
{
  "mcp": {
    "servers": {
      "filesystem": {
        "command": "npx",
        "args": ["-y", "@modelcontextprotocol/server-filesystem", "/path/to/allowed/dir"]
      },
      "github": {
        "command": "npx",
        "args": ["-y", "@modelcontextprotocol/server-github"],
        "env": {
          "GITHUB_PERSONAL_ACCESS_TOKEN": "your_token"
        }
      }
    }
  }
}

# OpenClaw Agent调用MCP工具
openclaw run --mcp filesystem --task "读取项目README.md"

# 或者在代码中调用
const result = await openclaw.mcp.call('filesystem', 'read_file', {
  path: '/path/to/file.md'
});
console.log(result);

# 创建自定义MCP服务器
import { McpServer } from '@modelcontextprotocol/sdk';

const server = new McpServer({
  name: 'my-custom-server',
  version: '1.0.0'
});

// 注册工具
server.tool('my_tool', async (params) => {
  // 你的工具逻辑
  return { result: 'success' };
});

// 启动服务器
server.listen(3000);
console.log('MCP服务器运行在端口3000');