What is Model Context Protocol (MCP) and how does it integrate with OpenAI tools?

Model Context Protocol (MCP) is an open standard for connecting AI models to external tools and data sources through a standardised interface. OpenAI has adopted MCP as a first-class integration in both the Responses API and the Codex CLI, enabling models to call tools exposed by MCP servers without requiring custom integration code per tool.

# Using a remote MCP server in the Responses API:
response = client.responses.create(
    model="gpt-5.5",
    tools=[
        {
            "type": "mcp",
            "server_url": "https://mcp.example.com/tools",
            "server_label": "my-internal-tools",
            "require_approval": "never",  # auto-approve tool calls
        }
    ],
    input="Query the production database for user count by region.",
)

# Secure MCP Tunnel (enterprise - for private servers):
# 1. Deploy tunnel-client on your internal network
# 2. Register tunnel in OpenAI platform
# 3. Reference as a remote MCP without exposing server publicly

# In Codex CLI during an active session:
# /mcp  - shows available MCP servers
# /mcp connect https://my-mcp-server.example.com/sse

MCP enables a composable ecosystem: any organisation can publish MCP servers for their internal systems (databases, ticketing systems, deployment tools) and connect them to Codex without OpenAI needing to build specific integrations for each tool.

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