| 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
-
Ask: Language Choice
-
Ask: MCP Configuration Type
- Hosted MCP (OpenAI-managed with server URL): Recommended for simplicity
- Streamable HTTP (Self-managed connection): For custom infrastructure
-
Install Package
- Python:
pip install openai-agents
- TypeScript:
npm install @openai/agents
-
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:
-
Ask: File Location
- NEW file: Ask where to create and what to name
- EXISTING file: Ask which file to integrate into (add MCP config)
-
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
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';
const agent = new Agent({
name: 'Assistant',
instructions: 'Use You.com tools to answer questions.',
tools: [
hostedMcpTool({
: ,
: ,
: {
: ,
},
}),
],
});
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
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
"""
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",
}
)
],
)
result = Runner.run(
agent,
)
(result.final_output)
__name__ == :
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
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
"""
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="AI News Assistant",
instructions=,
mcp_servers=[server],
)
result = Runner.run(
agent,
)
(result.final_output)
__name__ == :
asyncio.run(main())
TypeScript Hosted MCP Template (Complete Example)
import { Agent, run, hostedMcpTool } from '@openai/agents';
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'
);
}
async function main() {
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: {
: ,
},
}),
],
});
result = (
agent,
);
.(result.);
}
().(.);
TypeScript Streamable HTTP Template (Complete Example)
import { Agent, run, MCPServerStreamableHttp } from '@openai/agents';
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'
);
}
async function main() {
const mcpServer = new MCPServerStreamableHttp({
url: 'https://api.you.com/mcp',
name: 'You.com MCP Server',
requestInit: {
headers: {
Authorization: `Bearer ${ydcApiKey}`,
},
},
});
try {
mcpServer.();
agent = ({
: ,
:
,
: [mcpServer],
});
result = (
agent,
);
.(result.);
} {
mcpServer.();
}
}
().(.);
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] });
} 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:
export YDC_API_KEY="your-you-api-key-here"
export OPENAI_API_KEY="your-openai-api-key-here"
Get your API keys:
Validation Checklist
Before completing:
Testing Your Integration
Python:
python your-file.py
TypeScript:
npx tsx your-file.ts
tsc your-file.ts && node your-file.js
Common Issues
Cannot find module @openai/agents
Install the package:
npm install @openai/agents
bun add @openai/agents
yarn add @openai/agents
pnpm add @openai/agents
YDC_API_KEY environment variable is required
Set your You.com API key:
export YDC_API_KEY="your-api-key-here"
Get your key at: https://you.com/platform/api-keys
OPENAI_API_KEY environment variable is required
Set your OpenAI API key:
export OPENAI_API_KEY="your-api-key-here"
Get your key at: https://platform.openai.com/api-keys
MCP connection fails with 401 Unauthorized
Verify your YDC_API_KEY is valid:
- Check the key at https://you.com/platform/api-keys
- Ensure no extra spaces or quotes in the environment variable
- Verify the Authorization header format:
Bearer ${YDC_API_KEY}
Tools not available or not being called
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
Connection timeout or network errors
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,
},
max_retry_attempts=5,
) as server:
TypeScript:
const mcpServer = new MCPServerStreamableHttp({
url: 'https://api.you.com/mcp',
requestInit: {
headers: { Authorization: `Bearer ${process.env.YDC_API_KEY}` },
},
});
Additional Resources