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Authing MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Authing through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Vinkius supports streamable HTTP and SSE.

python
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 Authing "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Authing?"
    )
    print(result.data)

asyncio.run(main())
Authing
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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Authing MCP Server

Empower your AI agent to orchestrate your entire identity infrastructure with Authing, the premier cloud-native IDaaS platform. By connecting Authing to your agent, you transform complex user management, organizational modeling, and security auditing into a natural conversation. Your agent can instantly list users, retrieve detailed profile metadata, browse organizational structures, and monitor security audit logs without you ever needing to navigate the comprehensive Authing console. Whether you are conducting a compliance audit or managing application access, your agent acts as a real-time identity assistant, keeping your user data accurate and your systems secure.

Pydantic AI validates every Authing tool response against typed schemas, catching data inconsistencies at build time. Connect 10 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

  • User Orchestration — List and retrieve detailed information about users in your Authing user pool.
  • Organizational Management — Browse and monitor organizational units and hierarchies across your company.
  • Access Control Auditing — List roles, groups, and permission resources to identify authorization patterns.
  • Security Monitoring — Retrieve real-time security audit logs to monitor administrative and user actions.
  • System Configuration — Access high-level security settings and metadata for your identity projects.

The Authing MCP Server exposes 10 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.

How to Connect Authing to Pydantic AI via MCP

Follow these steps to integrate the Authing MCP Server with Pydantic AI.

01

Install Pydantic AI

Run pip install pydantic-ai

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

03

Run the agent

Save to agent.py and run: python agent.py

04

Explore tools

The agent discovers 10 tools from Authing with type-safe schemas

Why Use Pydantic AI with the Authing MCP Server

Pydantic AI provides unique advantages when paired with Authing through the Model Context Protocol.

01

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

02

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Authing integration code

03

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

04

Dependency injection system cleanly separates your Authing connection logic from agent behavior for testable, maintainable code

Authing + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Authing MCP Server delivers measurable value.

01

Type-safe data pipelines: query Authing with guaranteed response schemas, feeding validated data into downstream processing

02

API orchestration: chain multiple Authing tool calls with Pydantic validation at each step to ensure data integrity end-to-end

03

Production monitoring: build validated alert agents that query Authing and output structured, schema-compliant notifications

04

Testing and QA: use Pydantic AI's dependency injection to mock Authing responses and write comprehensive agent tests

Authing MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Authing to Pydantic AI via MCP:

01

create_user

Create a new user

02

get_audit_logs

Get security audit logs

03

get_security_settings

Get pool security settings

04

get_user

Get user details

05

list_applications

List registered applications

06

list_groups

List user groups

07

list_organizations

List organizations

08

list_resources

List permission resources

09

list_roles

List user roles

10

list_users

List application users

Example Prompts for Authing in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Authing immediately.

01

"List all users in our Authing pool."

02

"Show me the security audit logs from today."

03

"List all organizational units in the company."

Troubleshooting Authing MCP Server with Pydantic AI

Common issues when connecting Authing to Pydantic AI through the Vinkius, and how to resolve them.

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Authing + Pydantic AI FAQ

Common questions about integrating Authing MCP Server with Pydantic AI.

01

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.
02

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.
03

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Authing MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.

Connect Authing to Pydantic AI

Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.