How to Use the HTML XSS Sanitizer MCP in Pydantic AI

Q: How do I configure the HTML XSS Sanitizer MCP Server with Pydantic AI?

Install the pydantic-ai-slimmcp package. Create an MCPToolset pointing to your Vinkius HTTP endpoint, then pass it to your Agent constructor.

Guarantee safe HTML outputs with strict type validation in Pydantic AI using this MCP Server.

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Connect HTML XSS Sanitizer MCP to Pydantic AI

Create your Vinkius account to connect HTML XSS Sanitizer 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 HTML XSS Sanitizer with Pydantic AI

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Type-safe DOM cleaning via MCP Server

The `sanitizeHtml_html` tool accepts raw string inputs and returns strictly formatted, safe HTML. Your Pydantic AI agent routes user-generated content through this endpoint to strip malicious scripts and iframes. Because Pydantic AI enforces schema validation at runtime, you know exactly what you get back. If the tool fails to return a valid string, the framework throws a loud validation error instead of silently passing corrupted data.

Model-agnostic threat neutralization

Calling `sanitizeHtml_html` removes execution vectors from complex markup regardless of which LLM you use. The tool relies on actual DOM parsing rather than prompt instructions to clean the text. You do not have to trust a local model to understand XSS nuances. The MCP server handles the security logic, while your agent simply manages the flow of data using the `MCPToolset` integration.

Prevent silent database corruption

Using `sanitizeHtml_html` ensures bad markup never reaches your persistence layer. It catches nested tags and malformed attributes that break frontend layouts. Since correctness matters more than speed here, this explicit sanitization step is mandatory. Your agent fails fast if the input is completely broken, protecting your application from storing dangerous payloads.

Setup guide

Set up HTML XSS Sanitizer 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": {
        "html-xss-sanitizer-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent HTML XSS Sanitizer transactions")
print(result.output)

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Common questions about HTML XSS Sanitizer MCP in Pydantic AI

Install the `pydantic-ai-slim[mcp]` package. Create an `MCPToolset` pointing to your Vinkius HTTP endpoint, then pass it to your Agent constructor.

LLMs hallucinate and miss obscure XSS vectors. A dedicated parsing tool guarantees the removal of malicious code using deterministic rules.

The framework supports SSE and Streamable HTTP transports. Your agent waits for the full sanitized string before validating it against your Pydantic models.

Yes. Pydantic AI is model-agnostic. As long as your local model can call external tools, it can trigger the sanitization process.

The server runs in a stateless V8 sandbox. It receives your raw HTML, processes the DOM tree, returns the safe string, and instantly wipes the memory. Nothing is logged or saved.

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