How to Use the Bunny.net MCP in LlamaIndex

Q: Does this MCP Server support private Bunny.net storage zones in LlamaIndex?

It does. The agent uses getstoragezone to securely pull connection details, allowing it to index files even from restricted regions.

Index your Bunny.net edge configurations and storage files directly into LlamaIndex for semantic search.

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Connect Bunny.net MCP to LlamaIndex

Create your Vinkius account to connect Bunny.net 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 Bunny.net with LlamaIndex

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Semantic Search Over Edge Files via LlamaIndex

The `list_files` tool feeds live CDN file metadata directly into your vector index. By calling this action, the framework ingests file paths, sizes, and hashes, turning your remote storage into searchable knowledge. Your agent queries this index to find specific assets without scanning directories manually. It bridges the gap between static cloud files and conversational context.

Grounding Agent Decisions with Live CDN Metadata

The `get_pull_zone` tool verifies active SSL settings and Edge Rules before proposing changes. This MCP Server setup prevents the agent from making assumptions about your live routing policies. Grounding your queries in actual API data means the agent knows exactly what is deployed. It won't try to configure a domain that does not exist.

Automated Storage Discovery and Indexing

The `list_storage_zones` tool maps out your storage footprint to index physical regions. This allows the agent to build a comprehensive map of where your files actually live. It uses this index to decide where to route new files. You get a self-documenting storage setup that updates its own knowledge base automatically.

Setup guide

Set up Bunny.net 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 Bunny.net 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 Bunny.net tools.",
)
response = await agent.run("List recent Bunny.net 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 Bunny.net. 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 Bunny.net MCP in LlamaIndex

Load the tools into your agent using the MCP tool spec. The agent runs `list_files` to retrieve metadata, which you then convert into document nodes for your vector store.

Yes, if a query reveals outdated edge content, the agent can immediately call `purge_pull_zone`. This keeps your index and your CDN in sync.

It does. The agent uses `get_storage_zone` to securely pull connection details, allowing it to index files even from restricted regions.

The tool returns structured JSON payloads. LlamaIndex parses these lists chunk-by-chunk to avoid hitting LLM context window limits.

Your API tokens remain encrypted inside the Vinkius vault. The LlamaIndex runtime only receives the final metadata outputs, keeping your master keys completely hidden.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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