How to Use the Zingtree MCP in Pydantic AI

Q: Can I use Pydantic AI to process form data from Zingtree?

Yes. When you call getsessionformdata, the returned payload is automatically checked by Pydantic, guaranteeing that every key and value adheres to your defined Python types.

Q: Is Pydantic AI reliable for analyzing workflow structures from Zingtree?

It's highly reliable. When you call gettreestructure, the output is validated, giving your agent confidence that it truly understands the complex logic of the decision tree.

Ensure data correctness when analyzing Zingtree workflows using Pydantic AI.

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Connect Zingtree MCP to Pydantic AI

Create your Vinkius account to connect Zingtree 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 Zingtree with Pydantic AI

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Validate Form Data from Sessions with the MCP Server

When your agent retrieves user inputs, you can rely on type safety. The `get_session_form_data` tool pulls all form payloads, and Pydantic validation ensures that every field matches your expected schema. If data is corrupt, the agent fails loudly. This mechanism prevents silent corruption, which is vital when processing sensitive session data.

Define and Validate Tree Structures in Zingtree

The `get_tree_structure` tool provides the raw workflow definition. By validating this output against a Pydantic model, your agent guarantees it understands every node and path correctly. You can't afford to guess how a process flows. This type-safe approach makes building reliable agents that analyze Zingtree workflows much simpler.

Locate Specific Session Data for Review

Need details on one interaction? Use `get_session_details` to fetch structured data about a session. The agent then uses Pydantic validation to guarantee the returned fields are predictable and usable in code. Pairing this with `list_tree_sessions` lets you pull specific, validated batches of records for review.

Setup guide

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

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

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

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Common questions about Zingtree MCP in Pydantic AI

It validates every single piece of data returned by the MCP Server against your specified Python models. If `list_trees` returns unexpected fields, the agent raises a validation error immediately. No bad data gets through.

Yes. When you call `get_session_form_data`, the returned payload is automatically checked by Pydantic, guaranteeing that every key and value adheres to your defined Python types.

Pydantic validates the structure of the entire response. This means if you use `get_clean_session_path` or any other tool, the resulting object is guaranteed to conform to your type definitions.

It's highly reliable. When you call `get_tree_structure`, the output is validated, giving your agent confidence that it truly understands the complex logic of the decision tree.

This server handles session metadata, form payloads (strings, numbers), and structural definitions for trees. The primary type safety benefit is applying models to these complex dictionary outputs.

Use it with your favorite AI tools

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

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