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How to Use the Ele.me Open Platform / 饿了么 MCP in Pydantic AI

Type-safe Ele.me store management for Python. Validate every order payload with Pydantic AI and this MCP Server.

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Pydantic AI

Connect Ele.me Open Platform / 饿了么 MCP to Pydantic AI

Create your Vinkius account to connect Ele.me Open Platform / 饿了么 to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Validate order data with Pydantic AI

The `get_order_detail` and `list_recent_orders` tools return complex nested JSON from the Ele.me API. Pydantic AI forces these responses through strict runtime models. If the platform changes a date format or drops a required field, the agent fails loudly. You never pass corrupted data to your database. The framework catches the validation error instantly. You fix the model instead of hunting down silent bugs in production.

Control your shop state predictably

The `open_shop` and `close_shop` tools toggle your actual store visibility on the network. You check the current configuration using `get_shop_info`. The agent reads the exact metadata and confirms the store status matches your schedule. You pull your active inventory via `list_shop_categories`. The agent maps these categories to local database schemas. Because it runs through this MCP Server, you swap underlying LLMs without changing a single line of integration code.

Confirm orders and track deliveries

The `confirm_order` tool accepts the incoming transaction. If a customer requests a refund, `cancel_order` stops the process. Your agent executes these commands based on clear, typed parameters. You follow up using `track_delivery` to watch the courier state. Later, `get_order_comments` pulls the customer feedback. Every step returns typed data you can trust.

Setup guide

Set up Ele.me Open Platform / 饿了么 MCP in Pydantic AI

Prerequisites

  • Python 3.10+ installed
  • pydantic-ai-slim[fastmcp] package
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install Pydantic AI with FastMCP

    Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.

  2. 2

    Configure the FastMCPToolset

    Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.

  3. 3

    Create and run your agent

    Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py
from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "eleme-open-platform-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Ele.me Open Platform / 饿了么 tools.",
)

result = await agent.run("List recent Ele.me Open Platform / 饿了么 transactions")
print(result.output)

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Common questions about Ele.me Open Platform / 饿了么 MCP in Pydantic AI

Install `pydantic-ai-slim[mcp]`. Define an `MCPToolset` pointing to your HTTP endpoint. Pass this toolset array into your Agent definition.
The framework supports both Streamable HTTP and SSE transports. You configure this when initializing the toolset.
The agent throws a strict validation error. It halts execution immediately rather than hallucinating missing fields or silently passing bad data.
Yes. The framework is model-agnostic. You can route the Ele.me tools through OpenAI, Anthropic, or a local Llama instance.
The `get_order_comments` tool retrieves raw customer reviews and associated account identifiers. This MCP Server isolates execution inside an ephemeral V8 sandbox. Authentication is handled upstream, meaning your endpoint token is the only key, and memory dumps are purged instantly.

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