How do I find my Asset Panda Client ID and Secret?

Log in to Asset Panda, go to **Settings (cog icon) > API Configuration**. Your Client ID and Client Secret will be displayed at the bottom of the page.

What is a 'Group ID' in Asset Panda?

Groups (or Entities) are the categories for your records (e.g., Assets, Employees). You can find a group's ID in its URL when editing it in **Settings > Group Settings**.

How do I provide data for creating or updating assets?

Use the `jsonData` parameter with a valid JSON string where keys are field IDs (e.g., `{"field_123": "New Value"}`). You can find field IDs by using the `get_group` tool.

Asset Panda MCP Server for Pydantic AI 8 tools — connect in under 2 minutes

Name: Asset Panda
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 8 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Asset Panda 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 Asset Panda "
            "(8 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Asset Panda?"
    )
    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 Asset Panda MCP Server

The Asset Panda MCP Server provides a flexible natural language interface to your asset tracking and management platform. Empower your AI agent to manage your entire inventory, from high-level entity groups to individual asset details and location tracking.

Pydantic AI validates every Asset Panda tool response against typed schemas, catching data inconsistencies at build time. Connect 8 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.

Key Features

Group Management — List all organizational entities (Groups) to understand how your data is structured.
Asset Tracking — Retrieve detailed information for individual objects (assets), including custom field values.
Inventory Oversight — List and search for assets within specific groups to maintain an accurate inventory.
Asset Lifecycle — Create and update asset records directly from your chat interface to reflect real-world changes instantly.
Location Management — Track where your assets are across different sites and departments.
Secure OAuth 2.0 — Uses secure Client Credentials flow to ensure safe access to your organization's inventory data.

The Asset Panda MCP Server exposes 8 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 Asset Panda to Pydantic AI via MCP

Follow these steps to integrate the Asset Panda 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 8 tools from Asset Panda with type-safe schemas

Why Use Pydantic AI with the Asset Panda MCP Server

Pydantic AI provides unique advantages when paired with Asset Panda 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 Asset Panda integration code

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

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

Asset Panda + Pydantic AI Use Cases

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

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

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

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

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

Asset Panda MCP Tools for Pydantic AI (8)

These 8 tools become available when you connect Asset Panda to Pydantic AI via MCP:

create_object

Create a new object (asset) in a group

get_account_check

Verify Asset Panda account connection

get_group

Get metadata for a specific asset group

get_object

Get details for a specific object (asset)

list_groups

List all asset groups (entities) in Asset Panda

list_locations

List all locations (alias for list_groups)

list_objects

List all objects (assets) within a specific group

update_object

Update an existing object (asset)

Example Prompts for Asset Panda in Pydantic AI

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

"List all asset groups in my account."

"Show me the assets in the 'Laptops' group (ID: 12345)."

"Update the status of asset 'obj_9988' in group '123' to 'In Repair'."

Troubleshooting Asset Panda MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Asset Panda + Pydantic AI FAQ

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