How to Use the Autenti MCP in Pydantic AI

Get type-safe document signing for your Pydantic AI agents with Autenti.

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Connect Autenti MCP to Pydantic AI

Create your Vinkius account to connect Autenti 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 Autenti with Pydantic AI

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Type-safe signature processes with Pydantic AI

Every response from `get_user_account_profile` is validated against your Pydantic models at runtime. If the API structure shifts, your agent catches it immediately. This prevents your agent from acting on malformed data during the signature process. It ensures your document workflows remain stable and predictable.

Validate participants with Pydantic AI schema

Use `list_process_participants` to get a structured list of signers that your agent can safely process. Pydantic AI enforces the schema for every name and role returned. This guarantees your agent only attempts to interact with valid signer objects. It eliminates errors caused by unexpected API responses or empty fields.

Verify Autenti health with Pydantic AI tools

Run `check_api_health` as a pre-flight check in your agent's toolset. Pydantic AI validates the status response to ensure the service is ready for your signature requests. This keeps your agent from attempting actions during downtime. It provides a reliable way to manage connectivity in your production environment.

Setup guide

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

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

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

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Common questions about Autenti MCP in Pydantic AI

You initialize the MCPToolset with your HTTP endpoint and pass it into the toolsets parameter of your Agent. Pydantic AI handles the validation of every server response automatically. The server must be running externally as a managed instance.

Yes, the runtime validation ensures that only fields defined in your Pydantic model are processed. If Autenti returns unexpected data, the agent fails before the hallucination can propagate. It keeps your document automation logic strictly typed.

You can define multiple toolsets in your Pydantic AI Agent constructor. This allows your agent to switch between different Autenti environments or other MCP Servers as needed. It keeps your agent modular and flexible.

Your data is validated in memory and never written to disk by the Vinkius sandbox. Because the process is ephemeral, your signature records remain private and isolated. We enforce strict memory limits to ensure your data doesn't leak between tasks.

The server uses zero-trust architecture to protect your document IDs and participant metadata. Your agent only receives the specific fields your code requests. This minimizes the surface area for data exposure during every signature transaction.

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