How to Use the Daytona (Dev Workspaces) MCP in LlamaIndex

Turn your LlamaIndex knowledge base into an active controller for Daytona (Dev Workspaces) environments.

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Connect Daytona (Dev Workspaces) MCP to LlamaIndex

Create your Vinkius account to connect Daytona (Dev Workspaces) 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 Daytona (Dev Workspaces) with LlamaIndex

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Index your Daytona (Dev Workspaces) state

Feed the output of `list_sandboxes` and `list_volumes` directly into your LlamaIndex pipeline. This creates a searchable map of your current dev infrastructure. Your RAG system can now answer questions about which projects are active. It knows exactly where your work lives without you needing to check the dashboard manually.

Ground agent actions in real data

Use `get_sandbox` to pull fresh details before the agent makes a decision. By indexing these results, the agent avoids hallucinating about environment availability. It performs actions based on the current reality of your system. This makes your agents much more reliable when they need to modify or restart existing workspaces.

Query your workspace preview URLs

Retrieve active connections using `get_sandbox_preview_url` and add them to your index. Your agent can then provide direct links to running services in its responses. This creates a tight feedback loop where the agent not only manages the environment but also guides you to the right port. It turns raw infrastructure into a navigable knowledge base.

Setup guide

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

It calls the tools to fetch state and stores that output in your vector index. You can then perform semantic searches across your entire sandbox fleet.

Absolutely. You can list your snapshots and index their metadata so your agent knows exactly which versions are available for recovery.

The tools themselves become callable functions for your agents. Once indexed, the agent decides when to call them based on the context of your query.

You configure the client with your Vinkius endpoint. The SDK handles the rest of the connection logic so you can focus on building your index.

No. Your keys are handled at the server transport level. The index only stores the operational data returned by the tool calls.

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