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LandTech MCP Server for Pydantic AIGive Pydantic AI instant access to 12 tools to Get Api Status, Get Building Data, Get Ownership Title, and more

Built by Vinkius GDPR 12 Tools SDK

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

Ask AI about this App Connector for Pydantic AI

The LandTech app connector for Pydantic AI is a standout in the Real Estate category — giving your AI agent 12 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

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 LandTech "
            "(12 tools)."
        ),
    )

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

asyncio.run(main())
LandTech
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* 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 LandTech MCP Server

Connect your LandTech account to any AI agent and access property intelligence through natural conversation.

Pydantic AI validates every LandTech tool response against typed schemas, catching data inconsistencies at build time. Connect 12 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

  • Land Search — Search parcels by location, size, and zoning criteria
  • Ownership Analysis — Browse ownership records and title information
  • Planning Applications — Track planning permissions and application status
  • Site Assessment — Access environmental, flood risk, and constraint data
  • Development Tracking — Monitor construction activity and project pipelines

The LandTech MCP Server exposes 12 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.

All 12 LandTech tools available for Pydantic AI

When Pydantic AI connects to LandTech through Vinkius, your AI agent gets direct access to every tool listed below — spanning geospatial-intelligence, land-search, property-development, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

get_api_status

Check connection

get_building_data

Get property-level info

get_ownership_title

Get property title info

get_planning_details

Get planning info

get_planning_policy

Get policy details

get_price_comparables

Find similar sales

get_real_estate_market_data

Get regional insights

get_site_constraints

Check development risks

list_local_authority_plans

List regional policies

list_saved_sites

List portfolio sites

search_land_parcels

Find land for development

search_urban_planning

Find planning applications

Connect LandTech to Pydantic AI via MCP

Follow these steps to wire LandTech into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install Pydantic AI

Run pip install pydantic-ai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.py and run: python agent.py
04

Explore tools

The agent discovers 12 tools from LandTech with type-safe schemas

Why Use Pydantic AI with the LandTech MCP Server

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

01

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

02

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

03

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

04

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

LandTech + Pydantic AI Use Cases

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

01

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

02

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

03

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

04

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

Example Prompts for LandTech in Pydantic AI

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

01

"Search for development sites over 2 acres in London with residential zoning."

02

"Show ownership details and planning history for the Wandsworth site."

03

"List recent planning applications in Hackney and show environmental constraints."

Troubleshooting LandTech MCP Server with Pydantic AI

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

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

LandTech + Pydantic AI FAQ

Common questions about integrating LandTech MCP Server with Pydantic AI.

01

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.
02

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.
03

Can I switch LLM providers without changing MCP code?

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