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Agent Skill · 研究检索

ydc-openai-agent-sdk-integration(YDC OpenAI Agent SDK 集成)

ydc-openai-agent-sdk-integration 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

ydc-openai-agent-sdk-integration 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 2,641。

总安装 57,161周安装 2,335GitHub Stars 1下载 18,306核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:ydc-openai-agent-sdk-integration(YDC OpenAI Agent SDK 集成)
来源仓库:https://github.com/edwardirby/ydc-openai-agent-sdk-integration
安装命令:
openclaw skills install ydc-openai-agent-sdk-integration
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install ydc-openai-agent-sdk-integration

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

将 OpenAI Agents SDK 与 You.com MCP 服务器集成 - 针对 Python 和 TypeScript 的托管和流式 HTTP 支持。当开发人员提到 OpenAI Agents SDK、OpenAI 代理或将 OpenAI 与 MCP 集成时使用。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install ydc-openai-agent-sdk-integration;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

ydc-openai-agent-sdk-integration 怎么安装?

在终端执行 openclaw skills install ydc-openai-agent-sdk-integration。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

ydc-openai-agent-sdk-integration 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

ydc-openai-agent-sdk-integration 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

ydc-openai-agent-sdk-integration 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

ydc-openai-agent-sdk-integration 用的人多吗?

公开数据是累计安装 57,161 次,近一周安装 2,335 次,下载 18,306 次,GitHub 1 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

ydc-openai-agent-sdk-integration 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
ydc-openai-agent-sdk-integration

YDC OpenAI Agent SDK 集成 · 本页

57,1611接触敏感数据MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
ydc-openai-agent-sdk-integration
description
Integrate OpenAI Agents SDK with You.com MCP server - Hosted and Streamable HTTP support for Python and TypeScript. Use when developer mentions OpenAI Agents SDK, OpenAI agents, or integrating OpenAI with MCP.
license
MIT
compatibility
Python 3.10+ or Node.js 18+ with TypeScript
metadata
author
youdotcom-oss
category
sdk-integration
version
1.0.0
keywords
openai,openai-agents,agent-sdk,mcp,you.com,integration,hosted-mcp,streamable-http,web-search,python,typescript

Integrate OpenAI Agents SDK with You.com MCP

Interactive workflow to set up OpenAI Agents SDK with You.com's MCP server.

Workflow

  1. Ask: Language Choice

* Python or TypeScript?

  1. Ask: MCP Configuration Type

* Hosted MCP (OpenAI-managed with server URL): Recommended for simplicity * Streamable HTTP (Self-managed connection): For custom infrastructure

  1. Install Package

* Python: pip install openai-agents * TypeScript: npm install @openai/agents

  1. Ask: Environment Variables

For Both Modes: * YDC_API_KEY (You.com API key for Bearer token) * OPENAI_API_KEY (OpenAI API key)

Have they set them? * If NO: Guide to get keys: - YDC_API_KEY: https://you.com/platform/api-keys - OPENAI_API_KEY: https://platform.openai.com/api-keys

  1. Ask: File Location

* NEW file: Ask where to create and what to name * EXISTING file: Ask which file to integrate into (add MCP config)

  1. Create/Update File

For NEW files: * Use the complete template code from the "Complete Templates" section below * User can run immediately with their API keys set

For EXISTING files: * Add MCP server configuration to their existing code

Hosted MCP configuration block (Python):

   from agents import Agent, Runner
   from agents.mcp import HostedMCPTool

   # Validate: ydc_api_key = os.getenv("YDC_API_KEY")
   agent = Agent(
       name="Assistant",
       instructions="Use You.com tools to answer questions.",
       tools=[
           HostedMCPTool(
               tool_config={
                   "type": "mcp",
                   "server_label": "ydc",
                   "server_url": "https://api.you.com/mcp",
                   "headers": {
                       "Authorization": f"Bearer {ydc_api_key}"
                   },
                   "require_approval": "never",
               }
           )
       ],
   )

Hosted MCP configuration block (TypeScript):

   import { Agent, hostedMcpTool } from '@openai/agents';

   // Validate: const ydcApiKey = process.env.YDC_API_KEY;
   const agent = new Agent({
     name: 'Assistant',
     instructions: 'Use You.com tools to answer questions.',
     tools: [
       hostedMcpTool({
        serverLabel: 'ydc',
         serverUrl: 'https://api.you.com/mcp',
         headers: {
           Authorization: `Bearer ${ydcApiKey}`,
         },
       }),
     ],
   });

Streamable HTTP configuration block (Python):

   from agents import Agent, Runner
   from agents.mcp import MCPServerStreamableHttp

   # Validate: ydc_api_key = os.getenv("YDC_API_KEY")
   async with MCPServerStreamableHttp(
       name="You.com MCP Server",
       params={
           "url": "https://api.you.com/mcp",
           "headers": {"Authorization": f"Bearer {ydc_api_key}"},
           "timeout": 10,
       },
       cache_tools_list=True,
       max_retry_attempts=3,
   ) as server:
       agent = Agent(
           name="Assistant",
           instructions="Use You.com tools to answer questions.",
           mcp_servers=[server],
       )

Streamable HTTP configuration block (TypeScript):

   import { Agent, MCPServerStreamableHttp } from '@openai/agents';

   // Validate: const ydcApiKey = process.env.YDC_API_KEY;
   const mcpServer = new MCPServerStreamableHttp({
     url: 'https://api.you.com/mcp',
     name: 'You.com MCP Server',
     requestInit: {
       headers: {
         Authorization: `Bearer ${ydcApiKey}`,
       },
     },
   });

   const agent = new Agent({
     name: 'Assistant',
     instructions: 'Use You.com tools to answer questions.',
     mcpServers: [mcpServer],
   });

Complete Templates

Use these complete templates for new files. Each template is ready to run with your API keys set.

Python Hosted MCP Template (Complete Example)

"""
OpenAI Agents SDK with You.com Hosted MCP
Python implementation with OpenAI-managed infrastructure
"""

import os
import asyncio
from agents import Agent, Runner
from agents.mcp import HostedMCPTool

# Validate environment variables
ydc_api_key = os.getenv("YDC_API_KEY")
openai_api_key = os.getenv("OPENAI_API_KEY")

if not ydc_api_key:
    raise ValueError(
        "YDC_API_KEY environment variable is required. "
        "Get your key at: https://you.com/platform/api-keys"
    )

if not openai_api_key:
    raise ValueError(
        "OPENAI_API_KEY environment variable is required. "
        "Get your key at: https://platform.openai.com/api-keys"
    )


async def main():
    """
    Example: Search for AI news using You.com hosted MCP tools
    """
    # Configure agent with hosted MCP tools
    agent = Agent(
        name="AI News Assistant",
        instructions="Use You.com tools to search for and answer questions about AI news.",
        tools=[
            HostedMCPTool(
                tool_config={
                    "type": "mcp",
                    "server_label": "ydc",
                    "server_url": "https://api.you.com/mcp",
                    "headers": {
                        "Authorization": f"Bearer {ydc_api_key}"
                    },
                    "require_approval": "never",
                }
            )
        ],
    )

    # Run agent with user query
    result = await Runner.run(
        agent,
        "Search for the latest AI news from this week"
    )

    print(result.final_output)


if __name__ == "__main__":
    asyncio.run(main())

Python Streamable HTTP Template (Complete Example)

"""
OpenAI Agents SDK with You.com Streamable HTTP MCP
Python implementation with self-managed connection
"""

import os
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

# Validate environment variables
ydc_api_key = os.getenv("YDC_API_KEY")
openai_api_key = os.getenv("OPENAI_API_KEY")

if not ydc_api_key:
    raise ValueError(
        "YDC_API_KEY environment variable is required. "
        "Get your key at: https://you.com/platform/api-keys"
    )

if not openai_api_key:
    raise ValueError(
        "OPENAI_API_KEY environment variable is required. "
        "Get your key at: https://platform.openai.com/api-keys"
    )


async def main():
    """
    Example: Search for AI news using You.com streamable HTTP MCP server
    """
    # Configure streamable HTTP MCP server
    async with MCPServerStreamableHttp(
        name="You.com MCP Server",
        params={
            "url": "https://api.you.com/mcp",
            "headers": {"Authorization": f"Bearer {ydc_api_key}"},
            "timeout": 10,
        },
        cache_tools_list=True,
        max_retry_attempts=3,
    ) as server:
        # Configure agent with MCP server
        agent = Agent(
            name="AI News Assistant",
            instructions="Use You.com tools to search for and answer questions about AI news.",
            mcp_servers=[server],
        )

        # Run agent with user query
        result = await Runner.run(
            agent,
            "Search for the latest AI news from this week"
        )

        print(result.final_output)


if __name__ == "__main__":
    asyncio.run(main())

TypeScript Hosted MCP Template (Complete Example)

/**
 * OpenAI Agents SDK with You.com Hosted MCP
 * TypeScript implementation with OpenAI-managed infrastructure
 */

import { Agent, run, hostedMcpTool } from '@openai/agents';

// Validate environment variables
const ydcApiKey = process.env.YDC_API_KEY;
const openaiApiKey = process.env.OPENAI_API_KEY;

if (!ydcApiKey) {
  throw new Error(
    'YDC_API_KEY environment variable is required. ' +
      'Get your key at: https://you.com/platform/api-keys'
  );
}

if (!openaiApiKey) {
  throw new Error(
    'OPENAI_API_KEY environment variable is required. ' +
      'Get your key at: https://platform.openai.com/api-keys'
  );
}

/**
 * Example: Search for AI news using You.com hosted MCP tools
 */
async function main() {
  // Configure agent with hosted MCP tools
  const agent = new Agent({
    name: 'AI News Assistant',
    instructions:
      'Use You.com tools to search for and answer questions about AI news.',
    tools: [
      hostedMcpTool({
        serverLabel: 'ydc',
        serverUrl: 'https://api.you.com/mcp',
        headers: {
          Authorization: `Bearer ${ydcApiKey}`,
        },
      }),
    ],
  });

  // Run agent with user query
  const result = await run(
    agent,
    'Search for the latest AI news from this week'
  );

  console.log(result.finalOutput);
}

main().catch(console.error);

TypeScript Streamable HTTP Template (Complete Example)

/**
 * OpenAI Agents SDK with You.com Streamable HTTP MCP
 * TypeScript implementation with self-managed connection
 */

import { Agent, run, MCPServerStreamableHttp } from '@openai/agents';

// Validate environment variables
const ydcApiKey = process.env.YDC_API_KEY;
const openaiApiKey = process.env.OPENAI_API_KEY;

if (!ydcApiKey) {
  throw new Error(
    'YDC_API_KEY environment variable is required. ' +
      'Get your key at: https://you.com/platform/api-keys'
  );
}

if (!openaiApiKey) {
  throw new Error(
    'OPENAI_API_KEY environment variable is required. ' +
      'Get your key at: https://platform.openai.com/api-keys'
  );
}

/**
 * Example: Search for AI news using You.com streamable HTTP MCP server
 */
async function main() {
  // Configure streamable HTTP MCP server
  const mcpServer = new MCPServerStreamableHttp({
    url: 'https://api.you.com/mcp',
    name: 'You.com MCP Server',
    requestInit: {
      headers: {
        Authorization: `Bearer ${ydcApiKey}`,
      },
    },
  });

  try {
    // Connect to MCP server
    await mcpServer.connect();

    // Configure agent with MCP server
    const agent = new Agent({
      name: 'AI News Assistant',
      instructions:
        'Use You.com tools to search for and answer questions about AI news.',
      mcpServers: [mcpServer],
    });

    // Run agent with user query
    const result = await run(
      agent,
      'Search for the latest AI news from this week'
    );

    console.log(result.finalOutput);
  } finally {
    // Clean up connection
    await mcpServer.close();
  }
}

main().catch(console.error);

MCP Configuration Types

Hosted MCP (Recommended)

What it is: OpenAI manages the MCP connection and tool routing through their Responses API.

Benefits:

  • ✅ Simpler configuration (no connection management)
  • ✅ OpenAI handles authentication and retries
  • ✅ Lower latency (tools run in OpenAI infrastructure)
  • ✅ Automatic tool discovery and listing
  • ✅ No need to manage async context or cleanup

Use when:

  • Building production applications
  • Want minimal boilerplate code
  • Need reliable tool execution
  • Don't require custom transport layer

Configuration:

Python:

from agents.mcp import HostedMCPTool

tools=[
    HostedMCPTool(
        tool_config={
            "type": "mcp",
            "server_label": "ydc",
            "server_url": "https://api.you.com/mcp",
            "headers": {
                "Authorization": f"Bearer {os.environ['YDC_API_KEY']}"
            },
            "require_approval": "never",
        }
    )
]

TypeScript:

import { hostedMcpTool } from '@openai/agents';

tools: [
  hostedMcpTool({
    serverLabel: 'ydc',
    serverUrl: 'https://api.you.com/mcp',
    headers: {
      Authorization: `Bearer ${process.env.YDC_API_KEY}`,
    },
  }),
]

Streamable HTTP MCP

What it is: You manage the MCP connection and transport layer yourself.

Benefits:

  • ✅ Full control over network connection
  • ✅ Custom infrastructure integration
  • ✅ Can add custom headers, timeouts, retry logic
  • ✅ Run MCP server in your own environment
  • ✅ Better for testing and development

Use when:

  • Need custom transport configuration
  • Running MCP server in your infrastructure
  • Require specific networking setup
  • Development and testing scenarios

Configuration:

Python:

from agents.mcp import MCPServerStreamableHttp

async with MCPServerStreamableHttp(
    name="You.com MCP Server",
    params={
        "url": "https://api.you.com/mcp",
        "headers": {"Authorization": f"Bearer {os.environ['YDC_API_KEY']}"},
        "timeout": 10,
    },
    cache_tools_list=True,
    max_retry_attempts=3,
) as server:
    agent = Agent(mcp_servers=[server])

TypeScript:

import { MCPServerStreamableHttp } from '@openai/agents';

const mcpServer = new MCPServerStreamableHttp({
  url: 'https://api.you.com/mcp',
  name: 'You.com MCP Server',
  requestInit: {
    headers: {
      Authorization: `Bearer ${process.env.YDC_API_KEY}`,
    },
  },
});

await mcpServer.connect();
try {
  const agent = new Agent({ mcpServers: [mcpServer] });
  // Use agent
} finally {
  await mcpServer.close();
}

Available You.com Tools

After configuration, agents can discover and use:

  • mcp__ydc__you_search - Web and news search
  • mcp__ydc__you_express - AI-powered answers with web context
  • mcp__ydc__you_contents - Web page content extraction

Environment Variables

Both API keys are required for both configuration modes:

# Add to your .env file or shell profile
export YDC_API_KEY="your-you-api-key-here"
export OPENAI_API_KEY="your-openai-api-key-here"

Get your API keys:

  • You.com: https://you.com/platform/api-keys
  • OpenAI: https://platform.openai.com/api-keys

Validation Checklist

Before completing:

  • [ ] Package installed: openai-agents (Python) or @openai/agents (TypeScript)
  • [ ] Environment variables set: YDC_API_KEY and OPENAI_API_KEY
  • [ ] Template copied or configuration added to existing file
  • [ ] MCP configuration type chosen (Hosted or Streamable HTTP)
  • [ ] Authorization headers configured with Bearer token
  • [ ] File is executable (Python) or can be compiled (TypeScript)
  • [ ] Ready to test with example query

Testing Your Integration

Python:

python your-file.py

TypeScript:

# With tsx (recommended for quick testing)
npx tsx your-file.ts

# Or compile and run
tsc your-file.ts && node your-file.js

Common Issues

<details> <summary><strong>Cannot find module @openai/agents</strong></summary>

Install the package:

# NPM
npm install @openai/agents

# Bun
bun add @openai/agents

# Yarn
yarn add @openai/agents

# pnpm
pnpm add @openai/agents

</details>

<details> <summary><strong>YDC_API_KEY environment variable is required</strong></summary>

Set your You.com API key:

export YDC_API_KEY="your-api-key-here"

Get your key at: https://you.com/platform/api-keys

</details>

<details> <summary><strong>OPENAI_API_KEY environment variable is required</strong></summary>

Set your OpenAI API key:

export OPENAI_API_KEY="your-api-key-here"

Get your key at: https://platform.openai.com/api-keys

</details>

<details> <summary><strong>MCP connection fails with 401 Unauthorized</strong></summary>

Verify your YDC_API_KEY is valid:

  1. Check the key at https://you.com/platform/api-keys
  2. Ensure no extra spaces or quotes in the environment variable
  3. Verify the Authorization header format: Bearer ${YDC_API_KEY}

</details>

<details> <summary><strong>Tools not available or not being called</strong></summary>

For Both Modes:

  • Ensure server_url: "https://api.you.com/mcp" is correct
  • Verify Authorization header includes Bearer prefix
  • Check YDC_API_KEY environment variable is set
  • Confirm require_approval is set to "never" for automatic execution

For Streamable HTTP specifically:

  • Ensure MCP server is connected before creating agent
  • Verify connection was successful before running agent

</details>

<details> <summary><strong>Connection timeout or network errors</strong></summary>

For Streamable HTTP only:

Increase timeout or retry attempts:

Python:

async with MCPServerStreamableHttp(
    params={
        "url": "https://api.you.com/mcp",
        "headers": {"Authorization": f"Bearer {os.environ['YDC_API_KEY']}"},
        "timeout": 30,  # Increased timeout
    },
    max_retry_attempts=5,  # More retries
) as server:
    # ...

TypeScript:

const mcpServer = new MCPServerStreamableHttp({
  url: 'https://api.you.com/mcp',
  requestInit: {
    headers: { Authorization: `Bearer ${process.env.YDC_API_KEY}` },
    // Add custom timeout via fetch options
  },
});

</details>

Additional Resources

  • OpenAI Agents SDK (Python): https://openai.github.io/openai-agents-python/
  • OpenAI Agents SDK (TypeScript): https://openai.github.io/openai-agents-js/
  • MCP Configuration (Python): https://openai.github.io/openai-agents-python/mcp/
  • MCP Configuration (TypeScript): https://openai.github.io/openai-agents-js/guides/mcp/
  • You.com MCP Server: https://documentation.you.com/developer-resources/mcp-server
  • API Keys:

- You.com: https://you.com/platform/api-keys - OpenAI: https://platform.openai.com/api-keys

平台分布

OpenClaw

73.65%
按下载量换算13,482

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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