How do I get a Rebrickable API key?

Visit [**rebrickable.com/api**](https://rebrickable.com/api/), sign in with your Rebrickable account, and your API key will be displayed on the page. Copy it — it's a long alphanumeric string.

Can I search for sets by theme?

Yes! Use `list_sets` with `theme_id` to filter by theme. First use `list_themes` to find the theme ID (e.g. Star Wars = 170), then pass it to list_sets. You can also filter by year or part number.

Can I see the parts inventory for a set?

Yes! Use `get_set_parts` with the set number (e.g. "75192-1" for the Millennium Falcon). Returns every part with its part number, color ID, quantity and whether it's a spare. Set inc_minifig_parts to true to include minifig parts.

How many results can I get at once?

The API supports up to 1000 results per request. Use the `page_size` parameter (max 1000, default 100) and `page` for pagination. The total count and next/previous URLs are returned in each response.

Rebrickable LEGO MCP Server for Pydantic AI 11 tools — connect in under 2 minutes

Name: Rebrickable LEGO
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 11 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Rebrickable LEGO through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Rebrickable LEGO "
            "(11 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Rebrickable LEGO?"
    )
    print(result.data)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Rebrickable LEGO MCP Server

Connect to the Rebrickable LEGO API and explore the entire LEGO catalog through natural conversation.

Pydantic AI validates every Rebrickable LEGO tool response against typed schemas, catching data inconsistencies at build time. Connect 11 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Sets — Search and browse LEGO sets by theme, year or part number with piece counts and images
Parts — Explore the official LEGO parts catalog with part numbers, names and categories
Minifigures — Discover minifigures with their set numbers, themes and images
Themes — Browse all LEGO themes and sub-themes with set counts
Colors — List all LEGO colors with their IDs, names and RGB values
Set Parts — Get complete parts inventories for any LEGO set including spare parts

The Rebrickable LEGO MCP Server exposes 11 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Rebrickable LEGO to Pydantic AI via MCP

Follow these steps to integrate the Rebrickable LEGO MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 11 tools from Rebrickable LEGO with type-safe schemas

Why Use Pydantic AI with the Rebrickable LEGO MCP Server

Pydantic AI provides unique advantages when paired with Rebrickable LEGO through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Rebrickable LEGO integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Rebrickable LEGO connection logic from agent behavior for testable, maintainable code

Rebrickable LEGO + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Rebrickable LEGO MCP Server delivers measurable value.

Type-safe data pipelines: query Rebrickable LEGO with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Rebrickable LEGO tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Rebrickable LEGO and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Rebrickable LEGO responses and write comprehensive agent tests

Rebrickable LEGO MCP Tools for Pydantic AI (11)

These 11 tools become available when you connect Rebrickable LEGO to Pydantic AI via MCP:

get_minifig

g. "sw0001-1"). Returns the minifig name, theme, year, piece count and image URLs. Get details for a specific LEGO minifigure

get_part

g. "3001" for a 2x4 brick). Returns the part name, category, image URLs and available colors. Get details for a specific LEGO part

get_part_colors

Returns color IDs, color names and availability info. Useful for finding which colors a part is available in for MOC building. Get available colors for a LEGO part

get_set

g. "75192-1"). Returns the set name, year, theme, piece count, minifig count, image URLs and related info. Set numbers follow the format "NNNN-N" where NNNN is the set number and N is the variant. Get details for a specific LEGO set

get_set_parts

Each entry includes the part number, color ID, quantity and whether it's a spare part. Optionally include minifig parts. Use list_colors and list_parts to resolve color and part details. Get the parts inventory for a LEGO set

get_theme

Returns the theme name, parent theme (if sub-theme) and set count. Get details for a specific LEGO theme

list_colors

Useful for understanding color availability in sets and MOC building. List all LEGO colors in the catalog

list_minifigs

Returns minifig numbers, names, themes, year and image URLs. Optionally filter by part number. Use pagination with page and page_size (max 1000). Search LEGO minifigures

list_parts

Returns part numbers, names, categories and image URLs. Optionally filter by part number pattern. Use pagination with page and page_size (max 1000). Search LEGO parts in the catalog

list_sets

Optionally filter by theme ID, year, or part number. Returns set numbers, names, year, theme, piece count and image URLs. Use pagination with page and page_size (max 1000 per request). Search LEGO sets in the Rebrickable catalog

list_themes

g. Star Wars, City, Technic) and their sub-themes. Each theme includes its ID, name, parent theme ID (for sub-themes) and set count. Optionally filter by parent theme ID to get sub-themes of a specific theme. List LEGO themes and sub-themes

Example Prompts for Rebrickable LEGO in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Rebrickable LEGO immediately.

"Find all LEGO Star Wars sets from 2024."

"Show me the parts inventory for set 10497 (Galaxy Explorer)."

"What colors is LEGO part 3001 (2x4 brick) available in?"

Troubleshooting Rebrickable LEGO MCP Server with Pydantic AI

Common issues when connecting Rebrickable LEGO to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Rebrickable LEGO + Pydantic AI FAQ

Common questions about integrating Rebrickable LEGO MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Rebrickable LEGO MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.