How to Use the Diffbot MCP in Pydantic AI

Use the Diffbot MCP Server with Pydantic AI for type-safe, validated web data extraction in your Python agents.

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Connect Diffbot MCP to Pydantic AI

Create your Vinkius account to connect Diffbot 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 Diffbot with Pydantic AI

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Type-safe extraction with Pydantic AI

Don't guess what the API returns. Using `extract_product_data` with Pydantic AI ensures the result matches your model exactly, or it throws an error immediately. This prevents silent data corruption. If the web page layout changes, you know right away because the validation fails.

Deep entity enrichment for Pydantic AI

Use `enhance_person_profile` to pull validated contact or career data. Your Pydantic AI agent defines the schema, and the tool fills it with clean data. It turns messy web pages into structured objects. It's exactly what you need for reliable agent behavior.

Automated page analysis for Pydantic AI

Use `analyze_page_type` to determine how to process a link before you run a full extraction. Your agent makes the decision based on the result. It's a smart way to handle diverse web sources. Your agent stays in control of the logic at every step.

Setup guide

Set up Diffbot 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": {
        "diffbot-alternative-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Diffbot MCP in Pydantic AI

Because you want strict schema enforcement. Every bit of data coming from the web is validated against your Pydantic models at runtime.

Install the mcp package, then use MCPToolset to connect to your Vinkius endpoint. Add it to your agent's toolsets, and your models are ready.

It does. If a tool fails to return valid data, the agent catches the validation error and you can handle it with custom logic.

Every request is authenticated via your Vinkius endpoint token. The transport layer is isolated, ensuring your API key is never exposed to the web.

No. The MCP Server acts as a stateless conduit. It passes the extracted web content directly to your agent without keeping any logs.

Use it with your favorite AI tools

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

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Mastra AI sdk-typescript

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