Wherefour MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Get Inventory Item, Get Order, List Customers, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Wherefour as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this App Connector for LlamaIndex
The Wherefour app connector for LlamaIndex is a standout in the Industry Titans 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
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 Wherefour. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Wherefour?"
)
print(response)
asyncio.run(main())
* 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 Wherefour MCP Server
Connect your Wherefour account to any AI agent to automate your inventory management, production tracking, and lot traceability. Wherefour provides a specialized ERP platform for manufacturers and producers to maintain end-to-end transparency across their supply chain.
LlamaIndex agents combine Wherefour tool responses with indexed documents for comprehensive, grounded answers. Connect 12 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.
What you can do
- Inventory & Catalog Orchestration — List and search inventory items with detailed metadata, including product codes and manufacturing specifications.
- Lot Traceability — Access stock lot details and batch information to maintain comprehensive quality control and compliance.
- Order Management — Retrieve and monitor sales orders and production orders to keep your manufacturing workflow on track.
- Stakeholder Directory — Access and manage your database of customers, vendors, and suppliers programmatically.
- Financial Insights — Retrieve billing invoices and purchase records directly from the AI interface to monitor operational costs.
- Resource Navigation — Explore storage locations and manufacturing formulas using natural language commands.
The Wherefour MCP Server exposes 12 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.
All 12 Wherefour tools available for LlamaIndex
When LlamaIndex connects to Wherefour through Vinkius, your AI agent gets direct access to every tool listed below — spanning lot-traceability, production-tracking, manufacturing, 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.
Get details of a specific inventory item
Get details of a specific order
List all customers
List production formulas/recipes
List all inventory items
List customer invoices
List storage locations
List all sales and production orders
List purchase records
List all stock lots
List all vendors/suppliers
Search for inventory items
Connect Wherefour to LlamaIndex via MCP
Follow these steps to wire Wherefour into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Wherefour MCP Server
LlamaIndex provides unique advantages when paired with Wherefour through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Wherefour tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Wherefour tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Wherefour, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Wherefour tools were called, what data was returned, and how it influenced the final answer
Wherefour + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Wherefour MCP Server delivers measurable value.
Hybrid search: combine Wherefour real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Wherefour 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 Wherefour for fresh data
Analytical workflows: chain Wherefour queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Wherefour in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Wherefour immediately.
"Search our inventory for 'Organic Cane Sugar' and pull up the production formula that uses it for the upcoming beverage batch."
"Check the lot traceability for batch 'L-2024-QT3' of Arabica Coffee Beans and tell me which warehouse location it is currently stored in."
"List all pending production orders for 'Acme Supermarkets' and verify if their latest invoice from last month has been paid."
Troubleshooting Wherefour MCP Server with LlamaIndex
Common issues when connecting Wherefour to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpWherefour + LlamaIndex FAQ
Common questions about integrating Wherefour MCP Server with LlamaIndex.