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

Q: How do I fetch active realms safely?

Call getrealms through the agent to retrieve healthy catalyst nodes. The response is validated against strict user-count schemas, ensuring your model acts on reliable server metrics.

Q: How is my moderator rating data secured during rating updates?

The updateplacerating action uses end-to-end encrypted transport layers. Your moderator credentials and rating payloads are never decrypted by the marketplace middleware and pass straight to the Decentraland catalysts.

Run type-safe queries in Pydantic AI using this Decentraland-focused MCP Server with runtime validation.

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Connect Decentraland (Virtual World Content API) MCP to Pydantic AI

Create your Vinkius account to connect Decentraland (Virtual World Content API) to Pydantic AI 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 Pydantic AI

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Type-Safe Land Analysis via MCP Server

The `get_parcel_stats` tool returns user densities for virtual coordinate blocks. Pydantic AI validates these coordinate structures and integer user counts at runtime, preventing malformed API payloads from breaking your application. Your agent processes these stats alongside `get_hot_scenes` to build validated traffic reports. If the virtual world API structure shifts, your Python code fails immediately and loudly instead of processing corrupt coordinates.

Validated Event Management

The `create_event` tool requires structured inputs to successfully publish new virtual events. Pydantic AI enforces type safety on event names, start times, and location coordinates before sending the payload to the server. Your agent verifies credentials using `get_auth_request` after initializing the sequence with `create_auth_request`. This strict step-by-step verification ensures that only validated, authorized agents attempt to schedule events.

Strict Marketplace Schema Enforcement

The `get_marketplace_catalog` tool returns wearable lists that are parsed directly into Pydantic models. This architecture guarantees that price fields, token IDs, and owner addresses match your exact database schemas. Your agent queries `get_marketplace_items` to retrieve transaction records. Runtime validation shields your system from API drift, ensuring your trading scripts only execute on correctly typed historical data.

Setup guide

Set up Decentraland (Virtual World Content API) MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "decentraland-virtual-world-content-api-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Decentraland (Virtual World Content API) tools.",
)

result = await agent.run("List recent Decentraland (Virtual World Content API) transactions")
print(result.output)

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

Instantiate the MCP Server toolset with the HTTP endpoint. Pass this toolset directly into your Agent's `toolsets` argument to expose all fifteen virtual world tools.

Yes. The toolset validates the JSON schemas returned by the server, meaning your data remains strictly typed whether you use Anthropic, OpenAI, or local models.

If the MCP Server returns an unexpected status during authentication, the runtime validation throws a clean validation error. This prevents your agent from attempting unauthorized actions like event creation.

Call `get_realms` through the agent to retrieve healthy catalyst nodes. The response is validated against strict user-count schemas, ensuring your model acts on reliable server metrics.

The `update_place_rating` action uses end-to-end encrypted transport layers. Your moderator credentials and rating payloads are never decrypted by the marketplace middleware and pass straight to the Decentraland catalysts.

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