How to Use the Commerce7 MCP in LlamaIndex
Index your Commerce7 winery data into LlamaIndex for grounded, searchable insights.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Commerce7 MCP to LlamaIndex
Create your Vinkius account to connect Commerce7 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.
Searchable Commerce7 knowledge base
Use `search_customers` to pull profiles that LlamaIndex then vectorizes for semantic search. You get answers grounded in your actual customer history. Instead of guessing, your agent queries the index to find specific wine club members based on their order history or tasting room visits.
Query winery inventory with LlamaIndex
Run `list_inventory` to keep your knowledge base current with live stock levels. The agent treats these results as facts, preventing hallucinations when asked about wine availability. This creates a unified view where documents and API data exist in one searchable index. You get precise answers about what is ready for sale.
Contextualize Commerce7 orders
Fetch order details using `get_order` and let the agent index them for future reference. This allows your team to ask questions about historical shipping trends. Your RAG application uses these indexed records to provide context-aware responses. It turns raw API data into a conversational resource for your winery staff.
Set up Commerce7 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 Commerce7 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 Commerce7 tools.",
)
response = await agent.run("List recent Commerce7 data") Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Commerce7. 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.
Why Choose Vinkius
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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.
Built-in savings
60%
lower AI costs
Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.
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place for every integration
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Common questions about Commerce7 MCP in LlamaIndex
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