你的 AI 助手 (Claude / Cursor / 自研 Agent)
        │
        │  MCP Protocol (streamable-http)
        ▼
┌─────────────────────────────┐
│   TimeLinker MCP Server     │
│   https://mcp.timelinker.cn │
├─────────────────────────────┤
│  Tools:  publish_task       │──→ 发布真实任务到平台
│          search_tasks       │──→ 搜索匹配的任务
│          apply_task         │──→ 劳动者报名
│          accept_application │──→ 企业录用
│          approve_completion │──→ 验收结算
│  Resources:                 │
│          timelinker://tasks │──→ 实时任务数据
│          timelinker://talent│──→ 人才库
└─────────────────────────────┘
        │
        ▼
    真实世界执行（拍摄、配送、开发...）

{
  "mcpServers": {
    "timelinker": {
      "url": "https://mcp.timelinker.cn/mcp",
      "transport": "streamable-http",
      "headers": {
        "Authorization": "Bearer kt_live_你的API_KEY"
      }
    }
  }
}

{
  "mcpServers": {
    "timelinker": {
      "url": "https://mcp.timelinker.cn/mcp",
      "transport": "streamable-http",
      "headers": {
        "Authorization": "Bearer kt_live_你的API_KEY"
      }
    }
  }
}

pip install mcp

import asyncio
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client

async def main():
    # 连接 TimeLinker MCP Server
    async with streamablehttp_client(
        "https://mcp.timelinker.cn/mcp",
        headers={"Authorization": "Bearer kt_live_你的API_KEY"}
    ) as (read, write, _):
        async with ClientSession(read, write) as session:
            # 初始化连接
            await session.initialize()

            # 查看可用工具
            tools = await session.list_tools()
            print(f"可用工具: {[t.name for t in tools.tools]}")

            # 查看可用资源
            resources = await session.list_resources()
            print(f"可用资源: {[r.uri for r in resources.resources]}")

            # 搜索公开任务
            result = await session.call_tool("search_tasks", {
                "status": "open",
                "pageSize": 5
            })
            print(f"搜索结果: {result.content[0].text}")

            # 发布一个新任务
            result = await session.call_tool("publish_task", {
                "name": "春熙路商圈实地拍摄",
                "type": "摄影服务",
                "description": "需要一位摄影师前往春熙路商圈拍摄 20 张实景照片，用于商业宣传",
                "requirements": ["有商业摄影经验", "自备相机"],
                "budget": 200,
                "peopleNeeded": 1,
                "duration": "1天",
                "location": "成都市锦江区春熙路",
                "enterpriseId": 1
            })
            print(f"任务发布成功: {result.content[0].text}")

            # 读取资源：获取任务列表
            resource = await session.read_resource("timelinker://tasks")
            print(f"当前任务: {resource.contents[0].text}")

asyncio.run(main())

npm install @modelcontextprotocol/sdk

import { Client } from '@modelcontextprotocol/sdk/client/index.js';
import { StreamableHTTPClientTransport }
    from '@modelcontextprotocol/sdk/client/streamableHttp.js';

// 创建连接
const transport = new StreamableHTTPClientTransport(
    new URL("https://mcp.timelinker.cn/mcp"),
    {
        requestInit: {
            headers: {
                "Authorization": "Bearer kt_live_你的API_KEY"
            }
        }
    }
);

const client = new Client({ name: "my-ai-app", version: "1.0" });
await client.connect(transport);

// 列出所有可用工具
const tools = await client.listTools();
console.log("可用工具:", tools.tools.map(t => t.name));

// 列出所有可用资源
const resources = await client.listResources();
console.log("可用资源:", resources.resources.map(r => r.uri));

// 搜索任务
const searchResult = await client.callTool({
    name: "search_tasks",
    arguments: { status: "open", pageSize: 10 }
});
console.log("搜索结果:", searchResult.content);

// 发布任务
const publishResult = await client.callTool({
    name: "publish_task",
    arguments: {
        name: "H5 页面开发",
        type: "软件开发",
        description: "需要开发一个活动 H5 页面，含动画效果",
        budget: 15000,
        peopleNeeded: 1,
        duration: "2周",
        location: "远程",
        enterpriseId: 1
    }
});
console.log("发布结果:", publishResult.content);

// 读取资源
const taskList = await client.readResource({ uri: "timelinker://tasks" });
console.log("任务列表:", taskList.contents);

await client.close();

{
  "name": "publish_task",
  "arguments": {
    "name": "春熙路商圈实地拍摄",
    "type": "摄影服务",
    "description": "拍摄 20 张商业实景照片",
    "requirements": ["有商业摄影经验"],
    "budget": 200,
    "peopleNeeded": 1,
    "duration": "1天",
    "location": "成都市锦江区春熙路",
    "enterpriseId": 1
  }
}

# 获取所有公开任务
tasks = await session.read_resource("timelinker://tasks")

# 获取某个任务的详情
detail = await session.read_resource("timelinker://tasks/42")

# 获取企业仪表盘
dashboard = await session.read_resource("timelinker://dashboard/1")

# 获取可用人才列表
talent = await session.read_resource("timelinker://talent")

Authorization: Bearer kt_live_你的API_KEY

TimeLinker-MCP/
├── README.md              ← 本文档
├── mcp-proxy.mjs          ← stdio-to-HTTP 代理（用于 Claude Desktop）
├── server/                ← MCP Server 源码
│   ├── src/mcp/mcpServer.ts  ← MCP 协议实现（Tools + Resources）
│   └── src/middleware/mcpGateway.ts ← API Key 认证 + 计费网关
├── mcp-portal/            ← Web 控制台前端
│   └── src/pages/
│       ├── Landing.tsx    ← 官网首页
│       ├── Docs.tsx       ← 接入文档页
│       ├── Apply.tsx      ← API Key 申请页
│       └── console/       ← 用户控制台
└── timelinker.conf        ← Nginx 生产环境配置