MCP Servers

The Model Context Protocol (MCP) lets you connect AI models to external tool servers. Instead of defining tools inline, you point the model at an MCP server URL and it discovers and uses the available tools automatically.

How MCP works

You provide an MCP server URL in the tools array
The model connects to the server and discovers available tools
The model calls tools as needed to fulfill the request
Results are incorporated into the final response

Using an MCP server

Add an MCP tool type to your request:

from openai import OpenAI

client = OpenAI(
    api_key="shuttle-xxx",
    base_url="https://api.shuttleai.com/v1"
)

response = client.chat.completions.create(
    model="shuttleai/auto",
    messages=[{"role": "user", "content": "List all available models"}],
    tools=[
        {
            "type": "mcp",
            "server_url": "https://mcp.shuttleai.com/mcp",
            "server_label": "ShuttleAI MCP",
            "require_approval": "never"
        }
    ]
)

print(response.choices[0].message.content)

MCP tool parameters

Parameter	Type	Required	Description
`type`	string	Yes	Must be `"mcp"`
`server_url`	string	Yes	URL of the MCP server
`server_label`	string	No	Human-readable label for the server
`allowed_tools`	string[]	No	Restrict which tools the model can use
`require_approval`	string	No	`"never"` to auto-approve tool calls
`headers`	object	No	Custom headers to send to the MCP server

ShuttleAI’s official MCP server

We provide an official MCP server at:

https://mcp.shuttleai.com/mcp

Available tools on the official server:

Tool	Description
`chat_completion`	Generate text completions
`list_models`	List available models
`model_analytics`	Get model usage analytics

Authentication

Pass your API key to the MCP server via headers:

response = client.chat.completions.create(
    model="shuttleai/auto",
    messages=[{"role": "user", "content": "List all available models"}],
    tools=[
        {
            "type": "mcp",
            "server_url": "https://mcp.shuttleai.com/mcp",
            "server_label": "ShuttleAI",
            "require_approval": "never",
            "headers": {
                "Authorization": "Bearer shuttle-xxx"
            }
        }
    ]
)

Filtering tools

Use allowed_tools to restrict which tools the model can access:

tools=[
    {
        "type": "mcp",
        "server_url": "https://mcp.shuttleai.com/mcp",
        "allowed_tools": ["list_models", "chat_completion"],
        "require_approval": "never"
    }
]

Combining MCP with function tools

You can use MCP tools alongside regular function tools in the same request:

tools = [
    # Regular function tool
    {
        "type": "function",
        "function": {
            "name": "get_user_data",
            "description": "Get data for the current user",
            "parameters": {"type": "object", "properties": {}}
        }
    },
    # MCP tool
    {
        "type": "mcp",
        "server_url": "https://mcp.shuttleai.com/mcp",
        "require_approval": "never"
    }
]

Building your own MCP server

Any server that implements the Model Context Protocol specification can be used with ShuttleAI. This lets you give AI models access to your own internal tools, databases, and APIs.

Getting Started

Models

Pricing

Guides

How MCP works

Using an MCP server

MCP tool parameters

ShuttleAI’s official MCP server

Authentication

Filtering tools

Combining MCP with function tools

Building your own MCP server

​How MCP works

​Using an MCP server

​MCP tool parameters

​ShuttleAI’s official MCP server

​Authentication

​Filtering tools

​Combining MCP with function tools

​Building your own MCP server

How MCP works

Using an MCP server

MCP tool parameters

ShuttleAI’s official MCP server

Authentication

Filtering tools

Combining MCP with function tools

Building your own MCP server