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 LlamaIndex 8 tools — connect in under 2 minutes

Name: Asset Panda
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 8 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Asset Panda as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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 llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Asset Panda. "
            "You have 8 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Asset Panda?"
    )
    print(response)

asyncio.run(main())

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* 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.

LlamaIndex agents combine Asset Panda tool responses with indexed documents for comprehensive, grounded answers. Connect 8 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

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 LlamaIndex 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 LlamaIndex via MCP

Follow these steps to integrate the Asset Panda MCP Server with LlamaIndex.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

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

Why Use LlamaIndex with the Asset Panda MCP Server

LlamaIndex provides unique advantages when paired with Asset Panda through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Asset Panda tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Asset Panda tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Asset Panda, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Asset Panda tools were called, what data was returned, and how it influenced the final answer

Asset Panda + LlamaIndex Use Cases

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

Hybrid search: combine Asset Panda real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Asset Panda to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Asset Panda for fresh data

Analytical workflows: chain Asset Panda queries with LlamaIndex's data connectors to build multi-source analytical reports

Asset Panda MCP Tools for LlamaIndex (8)

These 8 tools become available when you connect Asset Panda to LlamaIndex 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 LlamaIndex

Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex

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

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Asset Panda + LlamaIndex FAQ

Common questions about integrating Asset Panda MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Asset Panda tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.