How to Use the Hanko (Passkey Auth) MCP in Pydantic AI

Q: Can I use Hanko (Passkey Auth) for session management in Pydantic AI?

Absolutely. Use publicvalidatesession to verify tokens, and map the output to your session model to keep the agent state secure.

Enforce strict identity schemas in Pydantic AI with the Hanko MCP Server.

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Connect Hanko (Passkey Auth) MCP to Pydantic AI

Create your Vinkius account to connect Hanko (Passkey Auth) 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 Hanko (Passkey Auth) with Pydantic AI

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Validate identity operations in Pydantic AI

Every tool response, including `admin_list_users`, is validated against your Pydantic models at runtime. This prevents malformed data from reaching your agent logic. If the server returns unexpected fields, the agent catches the error before any downstream processing happens. You get predictable, type-safe identity management.

Orchestrate flows with Pydantic AI

Use `flow_execute` to run complex Hanko actions as a single atomic unit. Your agent defines the expected input schema for each flow step. This ensures that complex registration or login sequences remain consistent. Any variance in the response triggers an immediate validation failure.

Manage keys securely in Pydantic AI

List and delete credentials using the typed outputs from `passkey_list_credentials`. Your agent treats every credential ID as a validated object. This removes the risk of passing invalid IDs to `passkey_delete_credential`. You maintain complete control over the credential lifecycle.

Setup guide

Set up Hanko (Passkey Auth) 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": {
        "hanko-passkey-auth-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent Hanko (Passkey Auth) transactions")
print(result.output)

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Common questions about Hanko (Passkey Auth) MCP in Pydantic AI

Pydantic AI validates every tool output against your defined models. If the server response doesn't match, the agent throws a clear validation error.

Yes. The server provides standard JSON output that maps perfectly to Pydantic models for type-safe interaction.

Absolutely. Use `public_validate_session` to verify tokens, and map the output to your session model to keep the agent state secure.

Pydantic AI catches the error response from the server. You can write custom exception handlers to manage the failure gracefully.

The server only processes WebAuthn public keys and session tokens. No private keys are ever handled by the tools.

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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