How to Use the Carbonara MCP in Pydantic AI

Q: Why is my MCP tool failing to load?

Make sure you use the modern MCPToolset class instead of the deprecated HTTP server methods. The Vinkius endpoint requires the unified connection approach.

Guarantee perfectly typed base64 code images with Pydantic AI and runtime validation.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Carbonara MCP to Pydantic AI

Create your Vinkius account to connect Carbonara 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 Carbonara with Pydantic AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Type-Safe Visuals with Pydantic AI

Generating base64 code images requires strict runtime schemas to prevent silent failures. When your agent requests a code image, the framework validates the incoming data against your defined models. The `cook_code_image` tool executes and returns the PNG data. If the API spits back malformed JSON or a broken string, the system throws a loud validation error immediately instead of passing garbage data downstream.

Model-Agnostic Image Generation

Locking yourself into one LLM provider limits your options. You swap between Anthropic, OpenAI, or local models without rewriting your visual rendering logic. The MCP Server handles the actual syntax highlighting and styling. Your agent just decides what code needs formatting, making the entire pipeline completely independent of the underlying intelligence.

Unified Toolset Integration

Older setups relied on fragmented HTTP connections. You now use the modern unified approach to bind external capabilities directly to your typed agents. Passing the configured toolset to the agent constructor wires everything up. The system automatically understands the required parameters for themes and window controls based on the exposed schema.

Setup guide

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

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

result = await agent.run("List recent Carbonara 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 Carbonara. 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 Carbonara 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 Carbonara MCP in Pydantic AI

Install the slim package with MCP support. Then instantiate `MCPToolset` with your HTTP endpoint URL and pass it to your Agent's `toolsets` array.

The framework aggressively validates the response payload. If the MCP Server returns anything other than the expected base64 string, the agent crashes loudly before saving a corrupt file.

The framework separates the reasoning engine from the tools. You run a local model to pick the code snippet, and it calls the external renderer exactly like a hosted model would.

Make sure you use the modern `MCPToolset` class instead of the deprecated HTTP server methods. The Vinkius endpoint requires the unified connection approach.

Every request hits an ephemeral V8 isolate that processes the syntax highlighting and immediately dies. Your code never hits a database, and the auth token restricts access to your specific environment.

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