How to Use the Browserless MCP in Pydantic AI

Q: How does Browserless prevent malformed HTML from breaking Pydantic AI?

The getpagecontent tool returns a structured string payload. Pydantic AI validates this string against your model's field definitions before parsing.

Q: Can I run raw scraping scripts safely with Browserless and Pydantic AI?

Yes, your agent uses runscrape to execute custom browser logic. The output is coerced into your defined Pydantic models at runtime.

Q: How do I check if the Browserless service is down using Pydantic AI?

Your agent can run checksystemhealth to get a structured boolean status. If it returns false, Pydantic AI raises a validation exception immediately.

Q: How does Browserless secure the browser session data handled by Pydantic AI?

Every session listed via listactivesessions is isolated at the container level. No session state, cookies, or rendered HTML are cached or shared across your different workspace environments.

Drive headless Chrome with Pydantic AI to get type-safe, validated web data.

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Connect Browserless MCP to Pydantic AI

Create your Vinkius account to connect Browserless 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 Browserless with Pydantic AI

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Type-safe web scraping with Pydantic AI

Stop guessing if your scraping output is corrupted. When your Pydantic AI agent calls `get_page_content`, the returned HTML is validated against your strict schema before your model even sees it. This MCP Server ensures that structural failures trigger immediate, loud validation errors. You can build reliable pipelines knowing that bad page loads won't inject garbage data into your database.

Validated visual rendering via Pydantic AI

Your Pydantic AI agent uses `take_screenshot` and `generate_pdf` over this MCP link to capture web pages, returning strongly-typed binary data. The framework guarantees that every visual asset matches your exact runtime specifications. Before saving the output, the framework verifies the response structure. This prevents corrupted or truncated image files from slipping through to your storage layers.

Monitored browser sessions in Pydantic AI

Keep tabs on your headless browser infrastructure with typed metrics. The agent calls `get_usage_stats` and `list_active_sessions` to parse your current account usage into clean Python objects. If the system reports high load, `check_system_health` and `get_account_config` provide the necessary telemetry. Your agent can then safely adjust its concurrency to match resource limits.

Setup guide

Set up Browserless 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": {
        "browserless-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Browserless MCP in Pydantic AI

The `get_page_content` tool returns a structured string payload. Pydantic AI validates this string against your model's field definitions before parsing.

Yes, your agent uses `run_scrape` to execute custom browser logic. The output is coerced into your defined Pydantic models at runtime.

Yes, you can connect Pydantic AI to the server using the standard HTTP or SSE transport layers.

Your agent can run `check_system_health` to get a structured boolean status. If it returns false, Pydantic AI raises a validation exception immediately.

Every session listed via `list_active_sessions` is isolated at the container level. No session state, cookies, or rendered HTML are cached or shared across your different workspace environments.

Use it with your favorite AI tools

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