How to Use the Apify MCP in Pydantic AI

Strictly validate web-extracted data from Apify using Pydantic AI models for reliable agent decisions.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Apify MCP to Pydantic AI

Create your Vinkius account to connect Apify 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.

GDPR Free for Subscribers

Setup Apify with Pydantic AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Type-safe scraping with Pydantic AI

Your agent triggers `run_actor` and waits for the result. The tool output is validated against your Pydantic schemas at runtime. This prevents malformed web data from breaking your application logic. You get an immediate error if the scraper schema drifts.

Retrieve datasets into Pydantic AI models

The `get_dataset_results` tool pulls data directly into your type-defined objects. It keeps your agent state consistent and predictable. Your code works with clean models instead of raw dictionaries. It makes debugging data issues trivial.

List and audit actor tasks in Pydantic AI

Use `list_actor_tasks` to see what is currently configured. Your agent can select the right task based on its current objective. This keeps your agent informed about available capabilities. It makes your automation setup transparent and manageable.

Setup guide

Set up Apify 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": {
        "apify-extended-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Apify. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Apify now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Apify MCP in Pydantic AI

Define an MCPToolset pointing to your Vinkius server URL. Add this toolset to your agent to allow it to call Apify tools with full type validation.

Pydantic AI will throw a validation error. This forces the agent to handle the failure rather than operating on corrupted or incomplete information.

The server supports both Streamable HTTP and SSE transports. Choose the one that fits your Pydantic AI architecture for the best performance.

Because the toolset is model-agnostic, it works with any engine. Your local model will receive the same type-safe results as a cloud-based one.

Data is pulled directly into the memory of your running agent process. We secure the connection with an endpoint token so only your agent can access the raw records.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript