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Apify MCP Server for Pydantic AIGive Pydantic AI instant access to 7 tools to Get Dataset Results, Get Run Details, List Actor Runs, and more

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Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Apify through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Ask AI about this App Connector for Pydantic AI

The Apify app connector for Pydantic AI is a standout in the Friends Mcp category — giving your AI agent 7 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Apify "
            "(7 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Apify?"
    )
    print(result.data)

asyncio.run(main())
Apify
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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Apify MCP Server

Connect your Apify account to any AI agent and simplify how you manage your web scraping, automation actors, and data storage through natural conversation.

Pydantic AI validates every Apify tool response against typed schemas, catching data inconsistencies at build time. Connect 7 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

  • Actor Control — List and trigger serverless actors for web scraping and automation directly from your agent.
  • Dataset Retrieval — Fetch the resulting data records (items) from your datasets to analyze or process values via AI.
  • Run Monitoring — Track the history and status of recent actor executions to ensure reliability.
  • Task Management — List and query configured actor tasks to reuse saved scraper settings.
  • Data Insights — Retrieve detailed metadata and logs for specific runs to debug complex automations.
  • Storage Visibility — List all datasets in your account to manage your collected web data.

The Apify MCP Server exposes 7 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 7 Apify tools available for Pydantic AI

When Pydantic AI connects to Apify through Vinkius, your AI agent gets direct access to every tool listed below — spanning data-extraction, serverless-actors, web-automation, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

get_dataset_results

Get items from a dataset

get_run_details

Get details for a specific run

list_actor_runs

List recent actor executions

list_actor_tasks

List configured actor tasks

list_actors

List Apify actors

list_datasets

List Apify datasets

run_actor

Trigger an actor run

Connect Apify to Pydantic AI via MCP

Follow these steps to wire Apify into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install Pydantic AI

Run pip install pydantic-ai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.py and run: python agent.py
04

Explore tools

The agent discovers 7 tools from Apify with type-safe schemas

Why Use Pydantic AI with the Apify MCP Server

Pydantic AI provides unique advantages when paired with Apify through the Model Context Protocol.

01

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

02

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Apify integration code

03

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

04

Dependency injection system cleanly separates your Apify connection logic from agent behavior for testable, maintainable code

Apify + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Apify MCP Server delivers measurable value.

01

Type-safe data pipelines: query Apify with guaranteed response schemas, feeding validated data into downstream processing

02

API orchestration: chain multiple Apify tool calls with Pydantic validation at each step to ensure data integrity end-to-end

03

Production monitoring: build validated alert agents that query Apify and output structured, schema-compliant notifications

04

Testing and QA: use Pydantic AI's dependency injection to mock Apify responses and write comprehensive agent tests

Example Prompts for Apify in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Apify immediately.

01

"List all actors in my Apify account."

02

"Run the 'Instagram Scraper' with input { "hashtags": ["#AI"] }."

03

"Show me the results from dataset 'ds_10293'."

Troubleshooting Apify MCP Server with Pydantic AI

Common issues when connecting Apify to Pydantic AI through the Vinkius, and how to resolve them.

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Apify + Pydantic AI FAQ

Common questions about integrating Apify MCP Server with Pydantic AI.

01

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.
02

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.
03

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Apify MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.