How to Use the GenerateBanners MCP in LlamaIndex

Q: How do I load GenerateBanners tools into LlamaIndex?

Install llama-index-tools-mcp via pip. Create a BasicMCPClient, wrap it in McpToolSpec, and pass the async tool list to your FunctionAgent.

Q: Can LlamaIndex search through my GenerateBanners templates?

It does. The agent calls searchtemplates and indexes the results. Users can then run semantic searches to find layouts that match their specific text requirements.

Q: How do I render multiple banners at once?

Your agent formats the retrieved data and passes it to renderbatch. It can then index the resulting image URLs for future reference.

Index ad templates and render history into your LlamaIndex RAG applications using this MCP Server.

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Connect GenerateBanners MCP to LlamaIndex

Create your Vinkius account to connect GenerateBanners 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.

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Setup GenerateBanners with LlamaIndex

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Vectorize your design templates

The `list_templates` tool feeds your available banner layouts directly into a LlamaIndex vector store. Your application indexes the design metadata so users can query for specific dimensions or styles using natural language. The `list_categories` tool provides metadata that your engine searches when a user asks for a holiday sale graphic. It retrieves the exact template ID without needing a rigid database query.

Query campaign data with LlamaIndex

The `list_projects` tool pulls your entire campaign history into the knowledge base. You can ask your RAG setup which projects ran last quarter, and it will parse the actual API data to give you an answer. The `get_project` tool fetches the exact configuration if you need specific details. This grounds your AI responses in real account activity rather than guessing what banners you made.

Generate images from the MCP Server

The `render_template` tool turns your text queries into actual image files. Your RAG system finds the right template, extracts the required fields via `get_template`, and requests the final render. The `get_account` tool lets you monitor your API usage limits. Your agent checks your available credits before executing a large `render_batch` job to avoid hitting rate limits.

Setup guide

Set up GenerateBanners 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 GenerateBanners 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 GenerateBanners tools.",
)
response = await agent.run("List recent GenerateBanners data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by GenerateBanners. 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.

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Common questions about GenerateBanners MCP in LlamaIndex

Install `llama-index-tools-mcp` via pip. Create a `BasicMCPClient`, wrap it in `McpToolSpec`, and pass the async tool list to your FunctionAgent.

It does. The agent calls `search_templates` and indexes the results. Users can then run semantic searches to find layouts that match their specific text requirements.

Your agent formats the retrieved data and passes it to `render_batch`. It can then index the resulting image URLs for future reference.

The MCP standard lets LlamaIndex natively understand the tool schemas. You skip writing custom API wrappers and get immediate access to project creation and rendering.

The server pulls your brand hex codes and ad copy to build the graphics. Every request routes through an ephemeral zero-trust environment that drops the payload the second the render completes.

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