How to Use the User-Agent Parser MCP in Pydantic AI

Q: How do I guarantee accurate client identification with User-Agent Parser for Pydantic AI?

The parseua tool decodes raw UA strings into JSON that is validated against your Pydantic models. This guarantees the Browser, OS, and Device fields are correctly typed and present before your agent uses them.

Q: Can User-Agent Parser handle complex log data with Pydantic AI?

Yes. You pass the raw UA string from your server logs to parseua. The tool extracts structured, validated JSON objects detailing the client's Browser, OS, and Device type, keeping everything type-safe.

Guarantee structured device data parsing with the User-Agent Parser using Pydantic AI.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect User-Agent Parser MCP to Pydantic AI

Create your Vinkius account to connect User-Agent Parser 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 User-Agent Parser with Pydantic AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Type-Safe UA Parsing for Pydantic AI

The `parse_ua` tool takes a raw HTTP header string and outputs JSON that strictly adheres to defined models. This means the output contains guaranteed fields for Browser, OS, and Device. When using this MCP Server with your agent, you eliminate silent failures. If the data is wrong, the system fails loudly, which is exactly what you want when correctness matters more than speed.

Validating Client Specs via Pydantic AI

The tool parses a raw UA string into a structured object that passes type validation at runtime. This prevents your agent from ever using hallucinated or corrupted client specs in its logic. It’s the safety net your production system needs. You're not just getting data; you're getting *validated* data.

MCP Server for Reliable Agent Inputs

Because it runs through an MCP Server, any agent can call `parse_ua` and receive a predictable JSON structure. This consistency is critical when your application needs to work with multiple models—OpenAI, Gemini, or local ones. The structured output ensures that regardless of the underlying model used, the client specs are always clean.

Setup guide

Set up User-Agent Parser 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": {
        "user-agent-parser-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent User-Agent Parser 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 UA Parser. 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 User-Agent Parser 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 User-Agent Parser MCP in Pydantic AI

The `parse_ua` tool decodes raw UA strings into JSON that is validated against your Pydantic models. This guarantees the Browser, OS, and Device fields are correctly typed and present before your agent uses them.

Yes. You pass the raw UA string from your server logs to `parse_ua`. The tool extracts structured, validated JSON objects detailing the client's Browser, OS, and Device type, keeping everything type-safe.

It accepts raw UA strings from HTTP headers or server logs. The core function of the MCP Server is to standardize this messy input into a clean, validated JSON format for your agent.

Absolutely. Since it's an external service exposed via an MCP Server, the output is always standardized and type-checked by Pydantic regardless of whether your agent uses a cloud API or a locally running model.

This MCP Server processes User-Agent strings. Specifically, it decodes raw HTTP User-Agent headers into structured client specifications: Browser, Operating System, and Device type.

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