How to use MCP with OpenAI Agents SDK

1pip install openai-agents
2
3# Optional: MCP Python SDK for building servers
4pip install "mcp[cli]"

1from agents.mcp import MCPServerStdio
2
3# Create the server connection
4async with MCPServerStdio(
5    command="npx",
6    args=["-y", "@modelcontextprotocol/server-filesystem", "/Users/you/projects"],
7) as server:
8    # server is now connected and tools are discovered
9    tools = await server.list_tools()
10    print(f"Available tools: {[t.name for t in tools]}")

1from agents import Agent, Runner
2from agents.mcp import MCPServerStdio
3
4async def main():
5    async with MCPServerStdio(
6        command="npx",
7        args=["-y", "@modelcontextprotocol/server-filesystem", "/Users/you/projects"],
8    ) as filesystem_server:
9
10        agent = Agent(
11            name="file-assistant",
12            instructions="You help users explore and understand their project files.",
13            mcp_servers=[filesystem_server],
14        )
15
16        result = await Runner.run(
17            agent,
18            "What TypeScript files are in the src directory?",
19        )
20        print(result.final_output)
21
22import asyncio
23asyncio.run(main())

1from agents.mcp import MCPServerStreamableHttp
2
3async with MCPServerStreamableHttp(
4    url="https://mcp.your-company.com/api",
5    headers={"Authorization": "Bearer your-token"},
6) as remote_server:
7    agent = Agent(
8        name="remote-assistant",
9        instructions="You help users with remote data.",
10        mcp_servers=[remote_server],
11    )
12    result = await Runner.run(agent, "What is the latest data?")
13    print(result.final_output)

1from agents import Agent, Runner
2from agents.mcp import MCPServerStdio
3
4async def main():
5    async with MCPServerStdio(
6        command="npx",
7        args=["-y", "@modelcontextprotocol/server-filesystem", "/Users/you/projects"],
8    ) as fs_server, MCPServerStdio(
9        command="npx",
10        args=["-y", "@modelcontextprotocol/server-brave-search"],
11        env={"BRAVE_API_KEY": "your-key"},
12    ) as search_server:
13
14        agent = Agent(
15            name="research-assistant",
16            instructions="You help users research topics using their files and the web.",
17            mcp_servers=[fs_server, search_server],
18        )
19
20        result = await Runner.run(
21            agent,
22            "Read my project's README and search the web for similar projects.",
23        )
24        print(result.final_output)
25
26import asyncio
27asyncio.run(main())

1from agents.mcp import MCPServerStdio
2
3async with MCPServerStdio(
4    command="npx",
5    args=["-y", "@modelcontextprotocol/server-postgres"],
6    env={
7        "POSTGRES_CONNECTION_STRING": "postgresql://user:pass@localhost:5432/mydb",
8    },
9) as db_server:
10    # db_server tools are now available
11    pass