How to Use the Carbonara MCP in LlamaIndex

Q: How do I limit which LlamaIndex agents can access Carbonara?

You can use the allowedtools filter when initializing your LlamaIndex MCP tool spec to restrict access to Carbonara.

Q: Does this tool support syntax highlighting for multiple languages?

Yes, the Carbonara cookcodeimage tool automatically detects or accepts parameters for dozens of programming languages to ensure perfect highlighting in LlamaIndex outputs.

Index and search your styled code snippets by combining LlamaIndex and Carbonara.

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 LlamaIndex

Create your Vinkius account to connect Carbonara to LlamaIndex 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 LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Index Styled Code Snippets into LlamaIndex

Store your Carbonara code visual metadata directly in your LlamaIndex vector store. Your LlamaIndex agent can run `cook_code_image` to generate a base64 PNG and then index the associated text description for semantic search. This means you can query your LlamaIndex knowledge base for specific functions and instantly retrieve both the explanation and the beautiful Carbonara image. It bridges the gap between raw LlamaIndex data and polished Carbonara presentation.

RAG Pipelines with Visual Code Outputs

Build LlamaIndex RAG applications that don't just return boring text blocks but render code via Carbonara. When a user asks for a code sample, your query engine can trigger `cook_code_image` to render a polished, syntax-highlighted visual. The Carbonara tool output feeds directly into your LlamaIndex response generation. Your LlamaIndex agent handles the formatting, giving your users clean, readable Carbonara code shots instead of unformatted markdown.

Expose Carbonara to LlamaIndex Function Agents

Turn your LlamaIndex agent into a technical designer using Carbonara. By loading the MCP Server tools, your `FunctionAgent` gets access to `cook_code_image` and can decide when an explanation needs a visual aid. The LlamaIndex agent inspects the code structure, selects the appropriate programming language for syntax highlighting, and runs the Carbonara tool to get a clean base64 image instantly.

Setup guide

Set up Carbonara MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Carbonara MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Carbonara tools.",
)
response = await agent.run("List recent Carbonara data")

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 LlamaIndex

Use llama-index-tools-mcp to connect to the Carbonara server. The client exposes `cook_code_image` which you convert to a tool list and pass to your LlamaIndex agent.

LlamaIndex indexes the text metadata and the base64 string from Carbonara. You can store the output in vector databases like Pinecone alongside your standard text nodes.

You can use the allowed_tools filter when initializing your LlamaIndex MCP tool spec to restrict access to Carbonara.

Yes, the Carbonara `cook_code_image` tool automatically detects or accepts parameters for dozens of programming languages to ensure perfect highlighting in LlamaIndex outputs.

Yes, security is tight when processing code snippets in LlamaIndex. Your raw code strings are processed in memory inside a secure, isolated sandbox and destroyed immediately after Carbonara renders the PNG.

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