Magicplan MCP Server for Pydantic AI 10 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Magicplan through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 Magicplan "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in Magicplan?"
)
print(result.data)
asyncio.run(main())
* 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 Magicplan MCP Server
Connect your Magicplan workspace to any AI agent to automate your architectural and estimation workflows. This MCP server enables your agent to interact with floor plans, retrieve precise spatial measurements, and access detailed financial estimates directly from natural language interfaces.
Pydantic AI validates every Magicplan tool response against typed schemas, catching data inconsistencies at build time. Connect 10 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
- Project Oversight — List all architectural projects and retrieve detailed metadata and status updates
- Spatial Intelligence — Access full floor plan spatial data including floors, rooms, and individual object placements
- Precise Measurements — Retrieve numeric statistics such as area, perimeter, and volume for any plan or specific room
- Estimation Audit — Access comprehensive financial breakdowns including labor, materials, taxes, and itemized positions
- User Management — List collaborators and manage workspace access across your architectural teams
- Data Collection — Query inspection forms and survey data attached directly to your floor plans
The Magicplan MCP Server exposes 10 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 Magicplan to Pydantic AI via MCP
Follow these steps to integrate the Magicplan 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 10 tools from Magicplan with type-safe schemas
Why Use Pydantic AI with the Magicplan MCP Server
Pydantic AI provides unique advantages when paired with Magicplan 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 Magicplan integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Magicplan connection logic from agent behavior for testable, maintainable code
Magicplan + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Magicplan MCP Server delivers measurable value.
Type-safe data pipelines: query Magicplan with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Magicplan tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Magicplan and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Magicplan responses and write comprehensive agent tests
Magicplan MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect Magicplan to Pydantic AI via MCP:
get_estimate_details
Get full financial breakdown for an estimate
get_plan_form_data
Retrieve forms attached to a specific plan
get_plan_measurements
Get numeric measurements for a plan
get_project_details
Get metadata for a specific project
get_project_floor_plan
Get full spatial data for a project
get_workspace_info
Get configuration for the current workspace
list_available_forms
List all data collection forms (checklists)
list_magicplan_projects
List all floor plan projects
list_project_estimates
List all financial estimates for a project
list_workspace_users
List all users in the Magicplan workspace
Example Prompts for Magicplan in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Magicplan immediately.
"List all architectural projects in my Magicplan workspace."
"Show the floor plan measurements for project ID '123'."
"Get the financial breakdown for estimate 'est-987' in project '456'."
Troubleshooting Magicplan MCP Server with Pydantic AI
Common issues when connecting Magicplan to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiMagicplan + Pydantic AI FAQ
Common questions about integrating Magicplan MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
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?
Can I switch LLM providers without changing MCP code?
Connect Magicplan with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Magicplan to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.