How to Use the ArborNote MCP in Pydantic AI

Q: Can I list ArborNote projects in Pydantic AI?

Yes, you use the listarbornoteprojects tool. The output is typed, ensuring your agent handles the list correctly every time.

ArborNote for Pydantic AI. Type-safe field data management with runtime validation for every tree survey.

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Connect ArborNote MCP to Pydantic AI

Create your Vinkius account to connect ArborNote 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 ArborNote with Pydantic AI

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Validate ArborNote responses

Pydantic AI forces every response from `get_arbornote_client` to match your strict data models. If the API returns garbage, the agent stops before the error propagates. This is how you prevent hallucinations. You define the shape, and the server must comply.

Run type-safe project lookups

Use `get_arbornote_project` to retrieve specific site details. The framework ensures the data conforms to your expectations before your agent makes a decision. It is the most reliable way to handle remote API data. You get clear errors if the server sends something unexpected.

Sync schedules with Pydantic AI

Fetch upcoming site visits with `list_arbornote_schedules` and pipe them into your workflow. The type-safety guarantees your agent won't trip over a missing field. This server runs externally, keeping your agent logic decoupled. You connect via SSE or HTTP and start calling tools immediately.

Setup guide

Set up ArborNote 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": {
        "arbornote-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent ArborNote transactions")
print(result.output)

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Common questions about ArborNote MCP in Pydantic AI

You get runtime type validation for every tool response. It stops silent failures in your forestry data processing.

The server returns data that the framework validates against your Pydantic model. If it doesn't fit, the agent raises a validation error.

Yes, you use the `list_arbornote_projects` tool. The output is typed, ensuring your agent handles the list correctly every time.

Yes. It is model-agnostic, meaning you can swap the underlying LLM without changing how you interact with your data.

Your inventory data is encrypted in transit and gated by your unique endpoint token. No unauthorized access occurs during the validation process.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript

Mastra AI sdk-typescript

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