How to Use the Decodo (Smartproxy) MCP in Pydantic AI

Q: How do I connect Pydantic AI to the Decodo (Smartproxy) server?

It's a one-liner. Just create an MCPToolset instance with your Vinkius URL, like MCPToolset("http://..."). Then pass it in the toolsets list when you create your Agent.

Q: Do I need to write my own Pydantic models for the tool outputs?

No, it's all automatic. The MCPToolset inspects the server's OpenAPI schema and generates the Pydantic models for you at runtime.

Get type-safe access to your Decodo (Smartproxy) account in any Python agent with Pydantic AI.

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Connect Decodo (Smartproxy) MCP to Pydantic AI

Create your Vinkius account to connect Decodo (Smartproxy) 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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Setup Decodo (Smartproxy) with Pydantic AI

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Get Reliable Proxy Data, Every Time

This server's tools like `list_residential_proxies` and `list_datacenter_proxies` return structured data about your proxy inventory. Pydantic AI automatically validates every response against a Pydantic model. You get clean, predictable objects in your Python code. If the Decodo (Smartproxy) API ever returns an unexpected field or a malformed response, your code will raise a `ValidationError` immediately. No more silent failures or corrupted data making its way into your application. You build with confidence.

Build Model-Agnostic Decodo Agents

Pydantic AI lets you swap out the underlying LLM without changing your tool code. You can use the `get_scraper_stats` and `get_traffic_usage` tools with an agent powered by OpenAI, Anthropic, or a local model. The logic for managing your Decodo account remains the same. This means you can prototype with a fast, cheap model and switch to a more powerful one for production. The Pydantic AI framework handles the model-specific prompting, so your tool definitions stay portable.

Manage Your Decodo (Smartproxy) MCP Server with Pydantic

Your agent gets a complete toolkit for account oversight. It can check subscription status with `list_subscriptions` and audit users with `list_sub_users`. Each tool call results in a validated Pydantic object. This approach is all about correctness. You define the data shape you expect from the Decodo MCP server, and Pydantic AI enforces it at runtime. It's the best way to ensure your agent's understanding of your proxy infrastructure is always accurate.

Setup guide

Set up Decodo (Smartproxy) MCP in Pydantic AI

Prerequisites

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

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

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

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": {
        "decodo-smartproxy-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Decodo (Smartproxy) tools.",
)

result = await agent.run("List recent Decodo (Smartproxy) transactions")
print(result.output)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Decodo (Smartproxy). All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Decodo (Smartproxy) MCP in Pydantic AI

Pydantic AI automatically creates Pydantic models from the MCP server's tool definitions. When your agent gets a response from a tool like `list_dedicated_proxies`, it validates the data against that model. If anything doesn't match, it raises an error instead of passing bad data to your agent.

Yes. Pydantic AI is model-agnostic. You can connect the Decodo (Smartproxy) MCPToolset to an agent using any compatible LLM, including local models run with Ollama or llama-cpp-python.

It's a one-liner. Just create an `MCPToolset` instance with your Vinkius URL, like `MCPToolset("http://...")`. Then pass it in the `toolsets` list when you create your `Agent`.

No, it's all automatic. The `MCPToolset` inspects the server's OpenAPI schema and generates the Pydantic models for you at runtime.

The integration only touches your Decodo (Smartproxy) account information, proxy lists, and usage metrics. Your Vinkius API token authenticates with the MCP server, which runs in a secure, single-tenant sandbox on Vinkius. Pydantic AI itself never stores your credentials or data.

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