Where do I find my Anvyl Team ID?

You can find your Team ID in the URL when you are logged into the Anvyl dashboard (e.g., `app.anvyl.com/teams/{TEAM_ID}/...`) or in your workspace settings.

Can I update the status of a production milestone via AI?

Yes, you can use the `confirm_milestone` tool to mark a milestone as complete or `delay_milestone` if production is behind schedule, providing a reason and a new expected date.

How do I track the shipping status of my orders?

Use the `list_logistics` tool with your Purchase Order ID. It will return all tracking records and shipping updates associated with that specific order.

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

Name: Anvyl
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

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

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

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 Anvyl "
            "(10 tools)."
        ),
    )

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

asyncio.run(main())

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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 Anvyl MCP Server

The Anvyl MCP Server brings visibility and automation to your supply chain operations. By connecting your Anvyl account to your AI agent, you can seamlessly track production progress, manage parts and suppliers, and update critical milestones using natural language.

Pydantic AI validates every Anvyl 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

Order Visibility — List all purchase orders and drill down into specific order details to check status and quantities.
Milestone Management — Track production and shipping milestones. Confirm completions or record delays directly from your chat.
Supplier Coordination — Quickly retrieve supplier information and part specifications stored in Anvyl.
Logistics Tracking — Access tracking records and logistics data for any purchase order to keep your team informed on delivery timelines.

The Anvyl 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 Anvyl to Pydantic AI via MCP

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

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

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

Explore tools

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

Why Use Pydantic AI with the Anvyl MCP Server

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

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

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

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

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

Anvyl + Pydantic AI Use Cases

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

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

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

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

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

Anvyl MCP Tools for Pydantic AI (10)

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

confirm_milestone

Confirm a milestone for a purchase order

delay_milestone

Delay a milestone for a purchase order

get_part

Get details for a specific part

get_purchase_order

Get details for a specific purchase order

get_supplier

Get details for a specific supplier

list_logistics

List tracking records for a purchase order

list_milestones

List milestones for a purchase order

list_parts

List parts in the Anvyl account

list_purchase_orders

List Anvyl purchase orders for the team

list_suppliers

List suppliers in the Anvyl account

Example Prompts for Anvyl in Pydantic AI

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

"List all active purchase orders."

"Check the milestones for order PO-123."

"Delay milestone 'm_456' for order PO-789 by 1 week because of raw material shortage."

Troubleshooting Anvyl MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Anvyl + Pydantic AI FAQ

Common questions about integrating Anvyl MCP Server with Pydantic AI.

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.

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.

Can I switch LLM providers without changing MCP code?

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