MCP Support

LangDB seamlessly integrates with your MCP server, allowing you to efficiently route and manage requests through your existing infrastructure.

Model Context Protocol (MCP) is an open standard that enables AI models to seamlessly communicate with external systems. It allows models to dynamically process contextual data, ensuring efficient, adaptive, and scalable interactions. MCP simplifies request orchestration across distributed AI systems, enhancing interoperability and context-awareness.

With native tool integrations, MCP connects AI models to APIs, databases, local files, automation tools, and remote services through a standardized protocol. Developers can effortlessly integrate MCP with IDEs, business workflows, and cloud platforms, while retaining the flexibility to switch between LLM providers. This enables the creation of intelligent, multi-modal workflows where AI securely interacts with real-world data and tools.

For more details, visit the Model Context Protocol official page and explore Anthropic MCP documentation.

client = OpenAI(
    api_key=os.getenv("LANGDB_API_KEY"),
    base_url=os.getenv("LANGDB_API_URL")
)
extra_body = {
    "mcp_servers": [
        {
            "server_url": "wss://your-mcp-server.com/ws?config=your_encoded_config",
            "type": "ws"
        }
    ]
}
response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "what is langdb?"}],
    extra_body=extra_body
)

Below is an example of a trace visualization after using Exa MCP server hosted on smithery, showcasing a detailed breakdown of the request stages:

For a complete example of how to use MCP, refer to the Smithery guide.