Mapflow MCP Server for Pydantic AIGive Pydantic AI instant access to 7 tools to Create Processing, Create Project, Get Processing Result, and more
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Mapflow 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 Mapflow app connector for Pydantic AI is a standout in the Artificial Intelligence category — giving your AI agent 7 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Mapflow "
"(7 tools)."
),
)
result = await agent.run(
"What tools are available in Mapflow?"
)
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 Mapflow MCP Server
Connect your Mapflow account to any AI agent and manage geospatial AI processing through natural conversation.
Pydantic AI validates every Mapflow tool response against typed schemas, catching data inconsistencies at build time. Connect 7 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 Management — Create and manage mapping projects
- Image Processing — Trigger AI models on satellite and drone imagery
- Task Tracking — Monitor processing status and completion
- Dataset Browsing — Access generated vector datasets and polygons
- Model Management — Browse available AI models (buildings, roads, forests)
The Mapflow MCP Server exposes 7 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 7 Mapflow tools available for Pydantic AI
When Pydantic AI connects to Mapflow through Vinkius, your AI agent gets direct access to every tool listed below — spanning geospatial-ai, satellite-imagery, drone-mapping, 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.
Pass data as a JSON string. Start a new imagery analysis
Pass data as a JSON string. Create a new project
Get processing result data
Check status of a processing job
List available geospatial AI models
List all geospatial processings
List all MapFlow projects
Connect Mapflow to Pydantic AI via MCP
Follow these steps to wire Mapflow into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install Pydantic AI
pip install pydantic-aiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use Pydantic AI with the Mapflow MCP Server
Pydantic AI provides unique advantages when paired with Mapflow 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 Mapflow integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Mapflow connection logic from agent behavior for testable, maintainable code
Mapflow + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Mapflow MCP Server delivers measurable value.
Type-safe data pipelines: query Mapflow with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Mapflow tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Mapflow and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Mapflow responses and write comprehensive agent tests
Example Prompts for Mapflow in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Mapflow immediately.
"List available AI models and my active projects."
"Start processing building footprints for the Seattle project."
"Check status of task tsk_8901 and show dataset results."
Troubleshooting Mapflow MCP Server with Pydantic AI
Common issues when connecting Mapflow to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiMapflow + Pydantic AI FAQ
Common questions about integrating Mapflow 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.