How to Use the Zoho Inventory MCP in LlamaIndex
Ground your AI knowledge base with LlamaIndex using the MCP Server for Zoho Inventory data.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Zoho Inventory MCP to LlamaIndex
Create your Vinkius account to connect Zoho Inventory to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Indexing Zoho Inventory Data in LlamaIndex
LlamaIndex takes the output from any tool and turns it into searchable knowledge. After running `list_inventory_items`, the resulting item details—names, rates, descriptions—are indexed. You can then query past API results semantically to find specific inventory information. This means you don't have to re-run a list command; you just ask your agent a question like 'What was the price of Widget X last month?' and get an answer grounded in actual Zoho Inventory data.
Building RAG Applications with MCP Server
You can combine live API calls with static documents. For example, you might upload a policy manual (document) and then run `list_sales_orders` (API data). LlamaIndex combines these sources so your agent answers questions using both the policy *and* real-time order data. It creates one unified knowledge index that eliminates guesswork by always pointing back to source material.
Querying Zoho Inventory Order History
Want to know what was ordered last quarter? Run `list_sales_orders` and feed those results into your index. Later, you can ask the agent about a specific order without having the original ID handy; it will query the indexed data points from the MCP Server. This makes historical API lookups much easier than just reading raw JSON dumps.
Set up Zoho Inventory MCP in LlamaIndex
Prerequisites
- Python 3.10+ installed
-
llama-index-tools-mcppackage - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package providesBasicMCPClientandMcpToolSpec. - 2
Connect with BasicMCPClient
Point
BasicMCPClientto your Vinkius endpoint URL. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports. - 3
Convert to LlamaIndex tools
Call
mcp_tool_spec.to_tool_list_async()to convert all Zoho Inventory MCP tools into nativeFunctionToolobjects that any LlamaIndex agent can use. - 4
Run with any LLM
Create a
FunctionAgentwith the tools and your preferred LLM. SwapOpenAIforAnthropic,Gemini, or any LlamaIndex-supported provider.
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
# Connect to the MCP
mcp_client = BasicMCPClient(
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)
# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()
# Create and run the agent
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt="You have access to Zoho Inventory tools.",
)
response = await agent.run("List recent Zoho Inventory data") Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Zoho Inventory. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Common questions about Zoho Inventory MCP in LlamaIndex
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