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Moxie MCP Server for Pydantic AIGive Pydantic AI instant access to 12 tools to Create Client, Create Expense, Create Invoice, and more

Built by Vinkius GDPR 12 Tools SDK

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

Ask AI about this App Connector for Pydantic AI

The Moxie app connector for Pydantic AI is a standout in the Productivity category — giving your AI agent 12 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

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 Moxie "
            "(12 tools)."
        ),
    )

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

asyncio.run(main())
Moxie
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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 Moxie MCP Server

Connect your Moxie workspace to any AI agent and manage your freelance or agency business through natural conversation.

Pydantic AI validates every Moxie tool response against typed schemas, catching data inconsistencies at build time. Connect 12 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

  • Clients & Contacts — List clients, create new ones, search contacts
  • Projects & Tasks — Search/create projects, create tasks
  • Invoices — Search payable invoices, create new ones
  • Time & Expenses — Log time entries, record expenses
  • Tickets — Create support tickets
  • Users — List workspace team members

The Moxie MCP Server exposes 12 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.

All 12 Moxie tools available for Pydantic AI

When Pydantic AI connects to Moxie through Vinkius, your AI agent gets direct access to every tool listed below — spanning freelance-management, invoicing, time-tracking, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

create_client

Create a new client

create_expense

Log an expense

create_invoice

Create a new invoice

create_project

Create a new project

create_task

Create a new task

create_ticket

Create a support ticket

create_time_entry

Log time

list_clients

List all clients in Moxie

list_users

List workspace users

search_contacts

Search for contacts

search_invoices

Search for payable invoices

search_projects

Search for projects

Connect Moxie to Pydantic AI via MCP

Follow these steps to wire Moxie into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

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 12 tools from Moxie with type-safe schemas

Why Use Pydantic AI with the Moxie MCP Server

Pydantic AI provides unique advantages when paired with Moxie 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 Moxie 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 Moxie connection logic from agent behavior for testable, maintainable code

Moxie + Pydantic AI Use Cases

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

01

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

02

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

03

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

04

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

Example Prompts for Moxie in Pydantic AI

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

01

"List all clients and their projects."

02

"Log 2 hours of consulting on the Acme Corp project."

03

"Create an invoice for Beta Design."

Troubleshooting Moxie MCP Server with Pydantic AI

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

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Moxie + Pydantic AI FAQ

Common questions about integrating Moxie 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 Moxie MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.