Openai Agent Sdk Integration

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?

2. Ask: MCP Configuration Type

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

3. Install Package

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

4. 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

5. Ask: File Location

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

6. 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, the AI agent can use these tools:

mcp__ydc__you_search

Web and news search with filters:

• query: Search query string
• freshness: Filter by recency (day, week, month, year)
• country: Country code for localized results
• count: Number of results to return

mcp__ydc__you_express

Fast AI agent with optional web search:

• input: Query or instruction for the AI agent
• tools: Optional list of tools to use (e.g., ["search"])

mcp__ydc__you_contents

Web page content extraction:

• urls: Array of URLs to extract content from
• formats: Output formats - array of "markdown", "html", or "metadata"
• crawl_timeout: Optional timeout in seconds (1-60)

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

Install the package:

# NPM
npm install @openai/agents

# Bun
bun add @openai/agents

# Yarn
yarn add @openai/agents

# pnpm
pnpm add @openai/agents

Set your You.com API key:

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

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

Set your OpenAI API key:

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

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

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}

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

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
  },
});

Advanced: MCP Server Development Patterns

For developers creating custom MCP tools or contributing to @youdotcom-oss/mcp:

Schema Design

Always use Zod for input/output validation:

export const MyToolInputSchema = z.object({
  query: z.string().min(1).describe("Search query"),
  limit: z.number().optional().describe("Max results"),
});

Why this pattern?

• Zod provides runtime validation and TypeScript types
• .describe() adds documentation for MCP tool parameters
• Schema validation catches invalid inputs before API calls

Error Handling

Always use try/catch with typed error handling:

try {
  const response = await apiCall();
  return formatResponse(response);
} catch (err: unknown) {
  const errorMessage = err instanceof Error ? err.message : String(err);
  await logger({ level: "error", data: `API call failed: ${errorMessage}` });
  return {
    content: [{ type: "text", text: `Error: ${errorMessage}` }],
    isError: true,
  };
}

Why this pattern?

• MCP tools must return structured responses, never throw
• err: unknown ensures type safety in catch blocks
• User-friendly error messages in content

Response Format

Return both content and structuredContent:

return {
  content: [{ type: "text", text: formattedText }],
  structuredContent: responseData,
};

Why this pattern?

• content provides human-readable text for display
• structuredContent provides machine-readable data
• MCP clients can choose which format to use

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