How to Use the DigitalOcean MCP in LlamaIndex

Index your DigitalOcean infrastructure directly into LlamaIndex for semantic cloud querying.

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Connect DigitalOcean MCP to LlamaIndex

Create your Vinkius account to connect DigitalOcean 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 DigitalOcean with LlamaIndex

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Claude

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Query your cloud infrastructure

Turn your server list into a searchable knowledge base. By using `list_droplets` and `list_domains`, LlamaIndex indexes your current setup for natural language retrieval. Ask questions about your configuration and get answers based on the actual API output. It stops the agent from guessing your server names.

Ground AI in real-time data

Combine your documentation with live API results. The agent uses `get_droplet_details` to pull specific specs and stores them in your vector index. This creates a grounded context for every query. Your agent answers based on what is currently running, not on outdated records.

Manage resources via semantic search

Locate specific clusters or volumes by describing their function. The agent searches the index created from `list_kubernetes_clusters` and `list_volumes` to find the right resource. This maps your intent to specific resource identifiers. It makes managing fragmented cloud assets much faster.

Setup guide

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

Use the MCP tool spec to pull data and pass it into your indexer. It turns raw API responses into searchable vectors.

Yes. You load the MCP tools into your agent and it will query your infrastructure to provide context for your RAG documents.

You can use memory-based indexes for short sessions or persistent vector stores. It depends on your specific implementation needs.

It uses semantic filtering to narrow down results. You avoid overloading the context window by only retrieving relevant infrastructure nodes.

The server only touches your account metadata. That data is stored in your local vector index and never shared with the model provider.

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

Mastra AI sdk-typescript

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