How to Use the Decentraland (Virtual World Content API) MCP in LlamaIndex

Q: Can I filter Decentraland (Virtual World Content API) tools for my LlamaIndex agent?

Yes, you use the allowedtools filter during setup. This ensures your agent only has access to the specific API operations you want it to use.

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Connect Decentraland (Virtual World Content API) MCP to LlamaIndex

Create your Vinkius account to connect Decentraland (Virtual World Content API) 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 Decentraland (Virtual World Content API) with LlamaIndex

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Ground LlamaIndex in Decentraland data

Index the results of `get_parcel_stats` directly into your vector store. You stop relying on static documents and start querying the actual state of the virtual world. Your RAG application updates its internal knowledge every time the agent runs these tools. It makes your answers grounded in current API data rather than outdated training sets.

Search marketplace history with LlamaIndex

Pull NFT trading history via `get_marketplace_items` and embed it into your search index. You can ask your agent about specific item trends and get answers based on the latest records. This creates a queryable history of the marketplace. You aren't just looking at a snapshot; you're building a searchable database of virtual asset activity.

Map virtual world health for LlamaIndex

Use `get_catalyst_about` to keep your knowledge base informed about server health. You can query your index to see if specific realms are struggling before you route traffic. It turns raw server configuration logs into searchable context. Your agents know exactly what the network looks like because they hold the index in their memory.

Setup guide

Set up Decentraland (Virtual World Content API) 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 Decentraland (Virtual World Content API) 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 Decentraland (Virtual World Content API) tools.",
)
response = await agent.run("List recent Decentraland (Virtual World Content API) data")

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Common questions about Decentraland (Virtual World Content API) MCP in LlamaIndex

Use the MCP tool spec to convert our API calls into native LlamaIndex tools. These then feed directly into your indexing pipeline.

No. By indexing the tool outputs, your agent answers questions using the specific data fetched from the API rather than guessing.

Yes, you use the allowed_tools filter during setup. This ensures your agent only has access to the specific API operations you want it to use.

It depends on your ingestion frequency. You only store the specific API outputs you choose to index, keeping your vector database lean.

Vinkius encrypts all data in transit. Once the tool output reaches your index, it is protected by whatever security measures you have applied to your local vector store.

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